fix(CORRECTION-1/2): D2 producer contract + sentinel-tolerant reader; D3 telemetry wired into production path

ADAPT-1 baseline corrections (per handoff: fix D2+D3, record D1 as FIXED_DEPTH_ROUTE_INAPPLICABLE — no OUTWARD semantics change). CORRECTION-1 (D2): producer contract enforced - Worker prompts updated: artifact file must contain exactly one JSON document; StageCompleted markers go to stdout ONLY - _load_worker_artifact_file(): canonical reader requires pure JSON; LEGACY_COMPATIBILITY_ONLY permits exactly the known 'StageCompleted: <STAGE>' trailing sentinel (regex-anchored, no arbitrary salvage); corrupt JSON is never masked - Acceptance: pure JSON OK; exact sentinel OK; arbitrary trailing text rejected; corrupt JSON rejected; all 6 stage prompts carry the contract CORRECTION-2 (D3): StageAttempt telemetry wired into real production path - research_event_relay: marks tool windows on tool running/completed/error/ failed events (observational, never changes classification) - StageExecutor._run_relay_with_telemetry: marks model windows around relay.run(); attempt threaded through _execute_stage into all 8 stage methods (telemetry_attempt kwarg, default None) - PROVEN on a real production-path execution: ADVERSARIAL record shows wall=0.3006, model_time=0.3001 (1 window), tool_time=0.3001 (1 window) — overlapping by design, non-additive model respected - telemetry failures never raise into the stage path (observational) D1 NOT a code correction: recorded as FIXED_DEPTH_ROUTE_INAPPLICABLE_TO_LOCAL_EVIDENCE_TASKS — EXPECTED_ROUTING_LIMITATION / ADAPTIVE_REQUIREMENT. OUTWARD external- evidence semantics preserved unchanged. 1163 tests pass (was 1158); ruff clean.
2026-09-09 22:18:50 +01:00
1 parent 243474c644
commit f5ee557ee3
@@ -29,7 +29,7 @@ Your dossier MUST carry a top-level "disposition" field, exactly one of:
 ## Output
 Produce your stage artifact as structured text. End with:
 ```
-StageCompleted: ADVERSARIAL
+StageCompleted: ADVERSARIAL  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```

 If you cannot complete this stage, end with:
@@ -19,7 +19,7 @@ do NOT introduce candidates without evidence derivation
 ## Output
 Produce your stage artifact as structured text. End with:
 ```
-StageCompleted: INNOVATION
+StageCompleted: INNOVATION  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```

 If you cannot complete this stage, end with:
@@ -19,7 +19,7 @@ do NOT do web research, do NOT synthesize a design
 ## Output
 Produce your stage artifact as structured text. End with:
 ```
-StageCompleted: INWARD
+StageCompleted: INWARD  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```

 If you cannot complete this stage, end with:
@@ -49,5 +49,5 @@ Produce your stage artifact as structured text with:

 End with:
 ```
-StageCompleted: OUTWARD
+StageCompleted: OUTWARD  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```
@@ -19,7 +19,7 @@ do NOT gate on confidence percentages
 ## Output
 Produce your stage artifact as structured text. End with:
 ```
-StageCompleted: QUALIFY
+StageCompleted: QUALIFY  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```

 If you cannot complete this stage, end with:
@@ -19,7 +19,7 @@ do NOT introduce unevidenced claims
 ## Output
 Produce your stage artifact as structured text. End with:
 ```
-StageCompleted: SYNTHESIS
+StageCompleted: SYNTHESIS  (stdout ONLY — the artifact file must contain exactly one JSON document, nothing else)
 ```

 If you cannot complete this stage, end with:
@@ -0,0 +1 @@
+consumed at 1788986488.1490133
@@ -0,0 +1 @@
+consumed at 1788986487.9547882
@@ -0,0 +1 @@
+consumed at 1788986509.530513
@@ -0,0 +1,502 @@
+{
+  "stage": "OUTWARD",
+  "issue": 162,
+  "round": 1,
+  "generated_by": "MiMoCode headless stage dispatch",
+  "subquestion": {
+    "address": "Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)"
+  },
+  "required_source_classes": [
+    "repo",
+    "external"
+  ],
+  "discovery": {
+    "queries": [
+      {
+        "id": "Q1",
+        "tool": "webfetch",
+        "url": "https://duckduckgo.com/html/?q=qdrant+dense+sparse+multivector+vectors+hybrid+search+documentation",
+        "status": "ok",
+        "note": "DDG HTML SERP, 10 results"
+      },
+      {
+        "id": "Q2",
+        "tool": "webfetch",
+        "url": "https://duckduckgo.com/html/?q=qdrant+colbert+late+interaction+reranking",
+        "status": "ok",
+        "note": "DDG HTML SERP, 10 results"
+      },
+      {
+        "id": "Q3",
+        "tool": "webfetch",
+        "url": "https://duckduckgo.com/html/?q=qdrant+docker+local+deployment+memory+usage+resource+requirements+small+scale",
+        "status": "ok",
+        "note": "DDG HTML SERP, 10 results"
+      },
+      {
+        "id": "Q4",
+        "tool": "webfetch",
+        "url": "https://duckduckgo.com/html/?q=colbert+late+interaction+reranking+cost+latency+tradeoffs+benchmark",
+        "status": "ok",
+        "note": "DDG HTML SERP, 10 results"
+      },
+      {
+        "id": "Q5",
+        "tool": "webfetch",
+        "url": "https://duckduckgo.com/html/?q=sqlite-vec+vs+qdrant+embedded+vector+database+comparison",
+        "status": "failed",
+        "note": "DuckDuckGo bot CAPTCHA page returned; no results. Receipt preserved. Comparative embedded-vs-server query not executed; not retried."
+      }
+    ],
+    "sources_discovered": 25,
+    "sources_selected": 6,
+    "sources_read": 6
+  },
+  "repo_grounding": {
+    "note": "Required source class 'repo' satisfied via direct code receipts from the harness repo (/mnt/workdrive/issue161-harness).",
+    "receipts": [
+      {
+        "id": "R1",
+        "path": "src/rune/memory_store.py",
+        "evidence": "line 5 'file running sqlite-vec (dense vectors) + FTS5 (BM25) side by side'; line 10 'HYBRID RETRIEVAL: dense (vec0) + BM25 (FTS5) fused by RRF'; lines 122-124 sqlite_vec.load(db); lines 129/149 entries_fts/chunks_fts fts5 virtual tables; lines 677-679 BM25-via-FTS5 recall path; line 856 conjunctive BM25 handling",
+        "method": "grep"
+      },
+      {
+        "id": "R2",
+        "path": "pyproject.toml",
+        "evidence": "memory extra = [\"sqlite-vec>=0.1.0\"]; no qdrant dependency anywhere in pyproject",
+        "method": "grep"
+      },
+      {
+        "id": "R3",
+        "path": "src/rune/**/*.py",
+        "evidence": "case-insensitive grep for 'qdrant' across src/rune returned ZERO matches — no Qdrant code exists; the spike is a projection/comparative study, not an existing integration",
+        "method": "grep"
+      },
+      {
+        "id": "R4",
+        "path": "task_tree.json INWARD context",
+        "evidence": "keyword claims I1-I5 (memory_store.py, sleep_time.py, canary_p1_07.py, curator.py, rune_tui.py) carried forward; umbrella 'memory' matches 7 modules incl. memory_selector, retrieval_benchmark",
+        "method": "read"
+      }
+    ]
+  },
+  "sources": [
+    {
+      "id": "O1",
+      "url": "https://qdrant.tech/documentation/search/hybrid-queries/",
+      "title": "Hybrid Queries - Qdrant (official docs)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": true,
+      "read": true,
+      "read_receipt": "webfetch 200; full page captured (output truncated to tool-output file tool_g001a087e977ad001HEG21pT0W; core sections read in-context)",
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O2",
+      "url": "https://qdrant.tech/documentation/search/text-search/hybrid-search/",
+      "title": "Hybrid Search - Qdrant (official docs)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1",
+      "note": "dense+sparse via prefetch API + RRF; redundant with O1 which was read in full"
+    },
+    {
+      "id": "O3",
+      "url": "https://github.com/qdrant/qdrant",
+      "title": "qdrant/qdrant - official repository README",
+      "source_class": "external",
+      "type": "official_repository",
+      "authority": "official",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": true,
+      "read": true,
+      "read_receipt": "webfetch 200 x2: raw.githubusercontent.com/qdrant/qdrant/master/README.md (clean read) + github.com blob page (chrome-noisy read, same content)",
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O4",
+      "url": "https://deepwiki.com/qdrant/qdrant-client/5.4-hybrid-search",
+      "title": "Hybrid Search | qdrant/qdrant-client | DeepWiki",
+      "source_class": "external",
+      "type": "ai_generated_docs_mirror",
+      "authority": "tertiary",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O5",
+      "url": "https://search.qdrant.tech/md/documentation/search/hybrid-queries",
+      "title": "search.qdrant.tech mirror of hybrid-queries",
+      "source_class": "external",
+      "type": "vendor_mirror",
+      "authority": "official_duplicate",
+      "classification": "NOT_SELECTED_duplicate",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O6",
+      "url": "https://github.com/Gbrlmoraes/hybrid_search_with_qdrant",
+      "title": "Hybrid Search with Qdrant (community example repo)",
+      "source_class": "external",
+      "type": "community_example",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O7",
+      "url": "https://milos-mitrovic.online/blog/how-to-build-hybrid-search-qdrant-dense-sparse-vectors",
+      "title": "How to Build Hybrid Search in Qdrant (Dense + Sparse)",
+      "source_class": "external",
+      "type": "community_blog",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1"
+    },
+    {
+      "id": "O8",
+      "url": "https://frutik.github.io/awesome-search/Articles/Hybrid-Queries---Qdrant",
+      "title": "Hybrid Queries - Qdrant (awesome-search mirror)",
+      "source_class": "external",
+      "type": "aggregator_mirror",
+      "authority": "tertiary",
+      "classification": "NOT_SELECTED_duplicate",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q1",
+      "note": "snippet carries the RRF weight-tuning guidance (train/val split, tune_rrf_weights helper, default 1.0/1.0 without eval set) — consistent with O1"
+    },
+    {
+      "id": "O9",
+      "url": "https://qdrant.tech/documentation/tutorials-search-engineering/using-multivector-representations/",
+      "title": "Multivectors and Late Interaction - Qdrant (official tutorial)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": true,
+      "read": true,
+      "read_receipt": "webfetch 200; full page read in-context",
+      "discovered_via": "Q2"
+    },
+    {
+      "id": "O10",
+      "url": "https://qdrant.tech/documentation/fastembed/fastembed-colbert/",
+      "title": "Working with ColBERT - Qdrant (official docs, FastEmbed)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q2",
+      "note": "FastEmbed ColBERT generation path; embedding-model side, redundant with O9's working example"
+    },
+    {
+      "id": "O11",
+      "url": "https://weaviate.io/blog/late-interaction-overview",
+      "title": "An Overview of Late Interaction Retrieval Models: ColBERT, ColPali, and ColQwen (Weaviate blog)",
+      "source_class": "external",
+      "type": "independent_vendor_analysis",
+      "authority": "independent_with_caveat",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": true,
+      "read": true,
+      "read_receipt": "webfetch 200; full page read in-context",
+      "discovered_via": "Q4",
+      "note": "written by a COMPETING vector-DB vendor — useful as vendor-neutral-ish counterweight to Qdrant docs, but not fully independent"
+    },
+    {
+      "id": "O12",
+      "url": "https://arxiv.org/abs/2004.12832",
+      "title": "ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT (Khattab & Zaharia, SIGIR 2020)",
+      "source_class": "external",
+      "type": "primary_paper",
+      "authority": "primary",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": true,
+      "read": true,
+      "read_receipt": "webfetch 200; abstract page read in-context (full text = PDF, not fetched)",
+      "discovered_via": "Q4"
+    },
+    {
+      "id": "O13",
+      "url": "https://qdrant.github.io/fastembed/examples/ColBERT_with_FastEmbed/",
+      "title": "Late Interaction Text Embedding Models (FastEmbed example)",
+      "source_class": "external",
+      "type": "vendor_example",
+      "authority": "official",
+      "classification": "NOT_SELECTED_duplicate",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q2"
+    },
+    {
+      "id": "O14",
+      "url": "https://github.com/duksaramio/qdrant-hybrid-search-with-reranking-tutorial",
+      "title": "Qdrant hybrid search with ColBERT MaxSim reranking tutorial (community)",
+      "source_class": "external",
+      "type": "community_example",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q2"
+    },
+    {
+      "id": "O15",
+      "url": "https://qdrantdb.de/documentation/advanced-tutorials/reranking-hybrid-search/",
+      "title": "Reranking in Hybrid Search (qdrantdb.de mirror)",
+      "source_class": "external",
+      "type": "unofficial_mirror",
+      "authority": "tertiary",
+      "classification": "NOT_SELECTED_mirror_site",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q2"
+    },
+    {
+      "id": "O16",
+      "url": "https://qdrant.tech/documentation/installation/",
+      "title": "Installation - Qdrant (official docs)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3",
+      "note": "CPU/memory/storage/networking requirements for self-hosted deployments; not read — ops requirements partially covered by O3/O17/O18 snippets"
+    },
+    {
+      "id": "O17",
+      "url": "https://github.com/orgs/qdrant/discussions/168",
+      "title": "RAM usage setup · qdrant · Discussion #168",
+      "source_class": "external",
+      "type": "community_discussion",
+      "authority": "maintainer_answered",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3",
+      "note": "maintainer answer in snippet: no direct RAM-usage config in the service; docker --memory limits only make OOM happen earlier"
+    },
+    {
+      "id": "O18",
+      "url": "https://qdrant.tech/documentation/faq/database-optimization/",
+      "title": "Database Optimization - Qdrant (official FAQ)",
+      "source_class": "external",
+      "type": "vendor_documentation",
+      "authority": "official",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3",
+      "note": "quantization + on-disk vector storage as the RAM levers; two resource-consumption scenarios"
+    },
+    {
+      "id": "O19",
+      "url": "https://markaicode.com/errors/qdrant-docker-deployment-failed-fix/",
+      "title": "Fix Qdrant Docker OOMKilled (markaicode)",
+      "source_class": "external",
+      "type": "seo_blog",
+      "authority": "low",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3"
+    },
+    {
+      "id": "O20",
+      "url": "https://vucense.com/dev-corner/qdrant-production-setup-2026/",
+      "title": "Qdrant in Production 2026: Setup & Quantization",
+      "source_class": "external",
+      "type": "community_blog",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3",
+      "note": "snippet: int8 scalar quantization ~4x RAM reduction at small recall cost; ports 6333 REST / 6334 gRPC"
+    },
+    {
+      "id": "O21",
+      "url": "https://github.com/qdrant/skills/blob/main/skills/qdrant-performance-optimization/memory-usage-optimization/SKILL.md",
+      "title": "qdrant/skills - memory-usage-optimization SKILL.md",
+      "source_class": "external",
+      "type": "official_repo_doc",
+      "authority": "official",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q3",
+      "note": "payload indexes + HNSW graph also require memory beyond vectors; capacity-planning guidance"
+    },
+    {
+      "id": "O22",
+      "url": "https://reranker.uk/guides/late-interaction-rerank.html",
+      "title": "Late-interaction reranking — ColBERT & beyond (reranker.uk)",
+      "source_class": "external",
+      "type": "community_guide",
+      "authority": "community",
+      "classification": "APPLICABLE_WITH_ADAPTATION",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q4",
+      "note": "snippet: sub-50ms budget favors late interaction over cross-encoder; use late-interaction to prune to ~50 candidates first"
+    },
+    {
+      "id": "O23",
+      "url": "https://123ofai.com/articles/blocks/colbert-late-interaction",
+      "title": "ColBERT Late Interaction in ML Systems (123ofai)",
+      "source_class": "external",
+      "type": "community_blog",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q4"
+    },
+    {
+      "id": "O24",
+      "url": "https://neelmishra.github.io/blog/mlops/rag/reranking.html",
+      "title": "Reranking: Cross-Encoders, ColBERT, Cohere",
+      "source_class": "external",
+      "type": "community_blog",
+      "authority": "community",
+      "classification": "NOT_SELECTED_low_authority",
+      "selected": false,
+      "read": false,
+      "discovered_via": "Q4"
+    },
+    {
+      "id": "O25",
+      "url": "https://arxiv.org/abs/2112.01488",
+      "title": "ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction",
+      "source_class": "external",
+      "type": "primary_paper",
+      "authority": "primary",
+      "classification": "APPLICABLE_DIRECT",
+      "selected": false,
+      "read": false,
+      "discovered_via": "O11 resources section",
+      "note": "identified but not fetched — ColBERTv2 facts extracted via O11's summary; candidate for a later stage if quantization细节 matters"
+    }
+  ],
+  "evidence": [
+    {
+      "id": "E1",
+      "source": "O1",
+      "subquestion_address": "dense/sparse/multivector hybrid + fusion",
+      "claims": [
+        "Qdrant Query API supports nested prefetch sub-requests; a query with >=1 prefetch executes each prefetch then applies the main query/fusion over their results.",
+        "Hybrid dense+sparse search fuses via RRF or DBSF. RRF: score(d) = sum over rankings of 1/(k + rank_d); k default 2, zero-based ranks, per-prefetch weights default 1.0; k settable since v1.16.0, per-prefetch weights since v1.17.0.",
+        "DBSF (v1.11.0+): normalizes each retriever's returned scores by 3-sigma extremes ((s-(mu-3sigma))/6sigma), then sums; stateless, computed per-query from prefetch top-k; emits 0.5 if scores degenerate; not clipped to [0,1].",
+        "Official fusion-selection guidance: with an eval set use weighted RRF (tuned on train/val split); trusting raw score magnitudes use DBSF; otherwise RRF is the safe default. Neither RRF nor DBSF dominates universally.",
+        "Raw-score alpha-weighted dense+sparse combination is documented as UNRELIABLE: dense (cosine, bounded) and sparse (BM25, unbounded) scores live on different per-query scales — directly mirrors Rune's memory_selector raw-score cross-scale ranking bias (P1-03 #26).",
+        "Multi-stage pattern: dense prefetch (e.g. limit 100) then multivector (ColBERT) re-score; HNSW m=0 disables indexing for rescore-only vectors, freeing memory."
+      ]
+    },
+    {
+      "id": "E2",
+      "source": "O1",
+      "subquestion_address": "recency/temporal scoring",
+      "claims": [
+        "Formula query (v1.14.0+) layers recency decay, popularity, geo on top of a fused RRF prefetch using $score + exp_decay over payload datetime keys — a server-side mechanism with no equivalent in Rune's SQLite stack."
+      ]
+    },
+    {
+      "id": "E3",
+      "source": "O3",
+      "subquestion_address": "deployment posture / embedded feasibility",
+      "claims": [
+        "Qdrant is a Rust vector database, Apache-2.0 licensed, normally deployed client-server via Docker (REST :6333, gRPC :6334).",
+        "Qdrant Edge exists: a lightweight in-process version for edge devices and resource-constrained environments — runs INSIDE the application process, stores and queries locally, syncs with a Qdrant server; Python/Rust API via EdgeShard. This is the only Qdrant mode compatible with Rune's embedded/local-first posture.",
+        "Qdrant natively supports dense (semantic), sparse (full-text/lexical), and multivector (late-interaction models like ColBERT) vectors in one product.",
+        "Built-in quantization 'cuts RAM usage by up to 97%'; features include WAL persistence, payload filtering, MMR, multitenancy, io_uring async I/O."
+      ]
+    },
+    {
+      "id": "E4",
+      "source": "O9",
+      "subquestion_address": "multivector + ColBERT reranking mechanics",
+      "claims": [
+        "Qdrant supports multivectors natively: MultiVectorConfig with MultiVectorComparator.MAX_SIM; one logical document = hundreds of token-level vectors (e.g. colbert-ir/colbertv2.0 at 128 dims via FastEmbed).",
+        "Official tutorial warns: 'most people don't use them effectively, resulting in massive RAM overhead, slow inserts, and wasted compute' — indexing every token-level vector with HNSW causes high RAM usage and slow inserts.",
+        "Recommended pattern: keep HNSW ON for the dense vector, set hnsw_config m=0 on the ColBERT multivector (stored, not indexed) and use it only for reranking; retrieval + MaxSim rerank then happens in ONE query_points call (dense prefetch -> colbert rescore)."
+      ]
+    },
+    {
+      "id": "E5",
+      "source": "O12",
+      "subquestion_address": "ColBERT late-interaction foundation",
+      "claims": [
+        "ColBERT (SIGIR 2020, Khattab & Zaharia) independently encodes query and document with BERT, then applies a cheap fine-grained interaction (MaxSim) — document representations are precomputed offline.",
+        "Measured vs BERT-based rerankers: two orders-of-magnitude faster and four orders-of-magnitude fewer FLOPs per query, while remaining competitive in effectiveness.",
+        "ColBERT's pruning-friendly interaction enables end-to-end retrieval via vector-similarity indexes, not just reranking."
+      ]
+    },
+    {
+      "id": "E6",
+      "source": "O11",
+      "subquestion_address": "ColBERT cost/storage trade-offs (independent view)",
+      "claims": [
+        "Late interaction = dual-encoder with token-level embeddings kept unpooled; MaxSim: per query token take max similarity over document tokens, then sum.",
+        "Storage is the core disadvantage: one vector per token. Even with ColBERTv2 2-bit residual compression, a 128-dim multivector representation costs ~2-5x the storage of a single 768-1536-dim dense vector for the same documents (100-token docs; e.g. n=1000: 4.50 MB multivector-d128 vs 1.54 MB dense-d768).",
+        "ColBERTv2 residual compression reduced ColBERTv1's MS MARCO index from 154GB to 16-25GB (6-10x) — but this compression is a ColBERTv2-index feature, and Qdrant's native multivector storage docs (O9) do not mention residual compression for stored multivectors.",
+        "Side-benefit: token-level MaxSim scoring gives explainability (which tokens matched) analogous to keyword-match interpretability."
+      ]
+    },
+    {
+      "id": "E7",
+      "source": "O17",
+      "subquestion_address": "ops footprint (small-scale server)",
+      "claims": [
+        "Maintainer answer (snippet): Qdrant server has NO direct max-RAM configuration; container --memory limits only trigger OOM earlier. Resource control relies on quantization/on-disk modes (O18) — relevant friction for a memory-capped single-node spike."
+      ]
+    }
+  ],
+  "limitations": [
+    "Q5 (sqlite-vec vs qdrant embedded comparison) failed on a DuckDuckGo CAPTCHA — no direct comparative evidence between Rune's current substrate (sqlite-vec) and Qdrant was collected; comparison must be derived, not cited.",
+    "No source benchmarks Qdrant (or Qdrant Edge) at Rune's regime: single-node, sub-1M entities, embedded/local-first, many short-lived processes. All performance figures (97% RAM cut, 4x fewer FLOPs, etc.) are vendor- or paper-origin, measured on large-scale passage-search corpora, not agent-memory workloads.",
+    "O11 is published by Weaviate, a competing vector-DB vendor — treated as independent-with-caveat; its ColBERT storage figures are derivations from the ColBERTv2 paper, not first-party benchmarks.",
+    "O12 abstract only (PDF not fetched); quantitative claims taken from the abstract's own wording.",
+    "Qdrant Edge maturity is unproven in the collected evidence: a single README section, no version/maturity/production-usage data, no evidence it supports sparse or multivector vectors (example shows dense only, size=4). Whether Edge supports the full dense/sparse/multivector + fusion surface is an OPEN QUESTION.",
+    "Qdrant server (the fully-featured path) is client-server via Docker — an architectural posture mismatch with Rune's embedded SQLite stack; the spike's feasibility hinges on the Edge-vs-Server question, which the evidence does not settle.",
+    "Snippet-level evidence (O8, O10, O16-O18, O20-O22) was classified but not read; claims from those sources are marked as snippet-derived and unverified."
+  ],
+  "contradictions": [
+    "C1: Qdrant markets multivector+ColBERT as a first-class native feature (O3), while its own tutorial (O9) reports that default usage produces 'massive RAM overhead, slow inserts, and wasted compute' — the feature is native but the safe configuration (m=0 rescore-only) is non-default.",
+    "C2: ColBERTv2 residual compression achieves 6-10x storage reduction (O11/O25), but Qdrant's multivector documentation (O9) never mentions residual compression for stored multivectors — Qdrant-stored ColBERT vectors may carry raw or differently-compressed token vectors, so paper-level storage figures do not transfer to Qdrant storage.",
+    "C3: README (O3) positions Qdrant Edge as suitable for resource-constrained/embedded use, while community/maintainer evidence (O17) shows the server product has no RAM ceiling control — the two deployment modes have opposite resource-governance stories, and Edge's capability surface is undocumented in collected sources."
+  ],
+  "evidence_requirement_status": "SATISFIED: >=2 unique URLs read (6 external sources read: O1, O3, O9, O11, O12, plus O3 raw+page dual receipt) and repo class satisfied via R1-R4 code receipts. Per stage contract, no further research performed.",
+  "stage_contract_compliance": {
+    "real_searches_executed": true,
+    "query_receipts_preserved": true,
+    "source_ids_stable": true,
+    "reads_executed": true,
+    "read_receipts_preserved": true,
+    "no_synthesis_performed": true,
+    "no_code_modified": true,
+    "no_solution_designed": true,
+    "stopped_after_evidence_requirement": true
+  }
+}
+StageCompleted: OUTWARD
@@ -0,0 +1,63 @@
+{"type":"step_start","timestamp":1788986520376,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e7f335001EnGDfgdcn","messageID":"msg_g001a087e7ceaf001lDCQmjnW4","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"eecbe373b85913496f68b023b19450c25eecd973","type":"step-start"}}
+{"type":"text","timestamp":1788986521895,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e7f44b002kqge6b031","messageID":"msg_g001a087e7ceaf001lDCQmjnW4","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"I'll start by searching for a matching skill and checking project memory for context on issue #162 / the Rune project.","time":{"start":1788986520651,"end":1788986521892}}}
+{"type":"tool_use","timestamp":1788986521898,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"skill_search","callID":"call_5a4e1803c4324b6eb563262a","state":{"status":"completed","input":{"query":"Discover and classify external sources for research subquestion about Qdrant vector database associative memory (dense/sparse/multivector vectors, ColBERT late-interaction reranking); issue real searches, preserve query receipts, assign stable source IDs, extract evidence claims, no synthesis"},"output":"{\n  \"status\": \"matched\",\n  \"results\": [\n    {\n      \"skill_id\": \"memory-search\",\n      \"name\": \"memory-search\",\n      \"score\": 0.5818,\n      \"reason\": \"The skill description matches these query terms: database, memory, query.\"\n    },\n    {\n      \"skill_id\": \"firecrawl-search\",\n      \"name\": \"firecrawl-search\",\n      \"score\": 0.5314,\n      \"reason\": \"The skill description matches these query terms: discover, source, research, about, real.\"\n    },\n    {\n      \"skill_id\": \"super-research\",\n      \"name\": \"super-research\",\n      \"score\": 0.3854,\n      \"reason\": \"The skill description matches these query terms: external, source, research, about, real, evidence, no.\"\n    }\n  ],\n  \"loaded_skill_id\": null\n}","metadata":{"status":"matched","loadedSkillID":null,"truncated":false},"title":"Found 3 skills","time":{"start":1788986521894,"end":1788986521897}},"id":"prt_g001a087e7f450001zoqCoRIXi","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","messageID":"msg_g001a087e7ceaf001lDCQmjnW4"}}
+{"type":"tool_use","timestamp":1788986521953,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"memory","callID":"call_fb4b5425484c46f39a07aa7b","state":{"status":"completed","input":{"operation":"search","query":"Qdrant associative memory #162 Rune spike projection"},"output":"Found 10 matches (BM25-ranked, best first).\nA hit here is authoritative — use it even if a parallel/sibling query returned nothing.\nIf you need the FULL body (snippets are truncated), Read the path.\nIf you need an EXACT literal (a connection string, port, token, full command line, path) and the snippet/body only paraphrases or partially shows it, the curated memory may have dropped the precise form — query the history tool for the original message, which holds it verbatim.\n\n### /home/nick/.local/share/mimocode/memory/projects/global/MEMORY-rules-gitea-2026-09-05.md\nScope: projects/global, Type: memory, Score: 17.525\n...New issues #161 (backend harness), #<<162>> (<<Qdrant>> <<spike>>), #163 (graph <<spike>>). FREEZE deep sqlite-vec/graph optimization unless needed for correctness or benchmark baseline. Do NOT adopt KuzuDB (archived Oct 2025). Tech...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f98e46b46ffe7fdgz483s/checkpoint.md\nScope: sessions/ses_-ffe5f98e46b46ffe7fdgz483s, Type: checkpoint, Score: 13.052\n...2. **Storage-frontier sequence (P1, after #148–#152):** #161 (<<memory>> backend abstraction + comparative benchmark harness) → #<<162>> (<<Qdrant>> <<spike>> incl. ColBERT late-interaction reranking) → #163 (temporal graph <<spike>>: Neo4j vs FalkorDB, LadybugDB experimental...\n\n### /home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md\nScope: projects/add96ab3-25dd-4c38-9fa3-34c01811d081, Type: memory, Score: 7.072\n...<<rune>>/<<memory>>_store.py`), hybrid recall accelerated by a precomputed association graph (hops=1); separate headless SQLite graph tier at `<<memory>>/graph/graph.sqlite` (`src/<<rune>>/graph_<<memory>>.py`); no <<Qdrant>> dependency...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG/checkpoint.md\nScope: sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG, Type: checkpoint, Score: 6.723\n...Issue-161 OUTWARD research stage — context gathered (stage contract, issue-263 artifact exemplar, <<Rune>> <<memory>>-stack grounding); next: batch DDG SERP discovery on SQLite FTS5/sqlite-vec vs <<Qdrant>> vs graph backends...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cabf29bffeBquaPsPsG/checkpoint.md\nScope: sessions/ses_-ffe5f7cabf29bffeBquaPsPsG, Type: checkpoint, Score: 6.205\n...<<Rune>> has no <<Qdrant>> code (confirmed by grep).\n- **C6: Graph substrate family / structural-graph evaluation** — sources [O15]; evidence [E18, E20, E22]; classification APPLICABLE_WITH_ADAPTATION (graph tier exists in graph_<<memory>>.py...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5fdce6835cffezTlUd3Fwd/warm_neuron_research.md\nScope: sessions/ses_-ffe5fdce6835cffezTlUd3Fwd, Type: free, Score: 5.433\n...<<ASSOCIATIVE>> <<MEMORY>> IN COGNITIVE ARCHITECTURES\n\n### How SOAR, ACT-R, and Modern Agents Differ from Keyword Search\n\nThe fundamental difference between <<associative>> retrieval and keyword search:\n\n| Property | Keyword Search | <<Associative>> Retrieval |\n|---|---|---|\n| Match criterion...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1/checkpoint.md\nScope: sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1, Type: checkpoint, Score: 5.279\n...Promote to <<MEMORY>>.md ## Architecture decisions when proven cross-session-durable._\n\n- Chose project-<<memory>> protocol over skill loading: the stage prompt's contract (receipts, O-IDs, no synthesis) matches the established <<Rune>>...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7c9d2281ffessfv3vUH4/checkpoint.md\nScope: sessions/ses_-ffe5f7c9d2281ffessfv3vUH4, Type: checkpoint, Score: 5.247\n...Read `src/<<rune>>/<<memory>>_selector.py` in full (511 lines) — see §6 for the attack-relevant facts extracted.\n\nNot yet done: reading <<memory>>_store.py / orchestration/benchmark.py / graph_<<memory>>.py / v1...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f98e46b46ffe7fdgz483s/checkpoint-directives-spillover.md\nScope: sessions/ses_-ffe5f98e46b46ffe7fdgz483s, Type: checkpoint, Score: 5.120\n...Canonical durable state is the ONLY authority; <<Qdrant>>/graph are rebuildable projections. Migrate only on demonstrated benchmark advantage.\n- **ANTI-COMPLEXITY RULES (integrity handoff §10, binding):** a concern is not automatically a subsystem...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB/checkpoint.md\nScope: sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB, Type: checkpoint, Score: 4.496\n...Key load-bearing facts for the classification (from the dossier):\n- <<Rune>>'s graphLine truncated
+{"type":"step_finish","timestamp":1788986522011,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e7f961001ucwu6Fl4h","reason":"tool-calls","snapshot":"99d2134cb78c1e678cfc67cd6f3fa9bb974e82c7","messageID":"msg_g001a087e7ceaf001lDCQmjnW4","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":28727,"input":28475,"output":252,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788986529860,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e81842001jS52h02YA","messageID":"msg_g001a087e7f9dd001rZch1d7mk","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"6a4bc2f9a6440ca668c95bb630f37780381ff7af","type":"step-start"}}
+{"type":"text","timestamp":1788986530983,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e818ee002sdFh1gYJ8","messageID":"msg_g001a087e7f9dd001rZch1d7mk","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"The closest skill (super-research) doesn't match this bespoke stage contract — prior sessions established a project-memory protocol for OUTWARD stages. Let me pull the project memory and prior stage exemplar to follow the established format.","time":{"start":1788986530030,"end":1788986530981}}}
+{"type":"tool_use","timestamp":1788986530993,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"read","callID":"call_caad2e19217244fda593e1dd","state":{"status":"completed","input":{"file_path":"/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY.md"},"output":"<path>/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY.md</path>\n<type>file</type>\n<content>\n1: Topic: Rune research pipeline — headless structured research rounds (stages, stage artifacts, SQLite usage facts) against Gitea issues\n2: # Project memory\n3: _Durable project-level knowledge. Persists across all sessions in this project. Edit only content under italic instructions._\n4: \n5: ## Project context\n6: _What is this project? What's its goal? High-level identity._\n7: \n8: Rune project research pipeline (repo at `/mnt/workdrive/rune/`). Sessions in this project execute structured research rounds against Gitea issues, one stage at a time, dispatched as headless prompts carrying a process capsule (process_id, issue, round, current_stage, allowed_action_now, expected_completion_artifact).\n9: \n10: ## Rules\n11: _Hard constraints from user that every session must respect._\n12: \n13: - Stage prompts are authoritative: obey `allowed_action_now` strictly (e.g., DEFINE forbids codebase analysis and web research).\n14: - Stage artifacts end with the literal line `StageCompleted: <STAGE>` (or `StageFailed: <STAGE>` + `Reason:`). Never fabricate a stage outcome.\n15: \n16: ## Architecture decisions\n17: _Major design choices with rationale. The \"why\" matters more than the \"what\" for future sessions._\n18: \n19: (none yet)\n20: \n21: ## Discovered durable knowledge\n22: _Cross-task facts that survive across sessions. Promoted from session checkpoints' §7 when proven durable._\n23: \n24: - `src/rune/memory_selector.py` has a documented KNOWN RANKING BIAS (P1-03 #26 finding 9): merged candidates are ranked by RAW score across mode-dependent calibrated scales (lexical store ~4-6, dense/hybrid RRF ~0-0.13, self-scored 0-1), so cross-source candidate ORDER is biased while abstention is not (each source floored on its own scale; store rows carry `store_scored=True` and are exempt from the selector-side numeric check). Any retrieval-quality benchmark of `memory_store.recall` alone measures the store, not what production surfaces — selector merge order is a separate unmeasured stage. Also: `MAX_CANDIDATES=24`, `DEFAULT_BUDGET=4`, persona lane always runs a second typed query for self/personality, shard routing deliberately bypassed.\n25: - Issue-163 ADVERSARIAL accepted (artifact `research/issue-163/adversarial.json`, harness repo): 13 attacks (A1–A13) settled INN-1's two halves. Survivors: C4 (SURVIVES_WITH_DOWNGRADE — \"bi-temporal E14 1:1\" claim is false; actual = transaction-time append log with same-triple supersession), C5 (SURVIVES_ONLY_IN_CORRECTED_FORM — INN-1's as-of filter is falsified: supersede never writes valid_until so superseded edges are NULL-open and pass the filter forever), C6 (SURVIVES_CONDITIONAL — graph is EMPTY and memory_selector re-floors graph candidates), C9 (SURVIVES_TRACK_ONLY). REJECTED (do NOT resurrect): INN-1#temporal-filter-as-specified. Accepted mitigations M1–M7: M1 fix temporal semantics before any as-of ships ((a) set valid_until=now on supersede at graph_memory.py:206-208, OR (b) transaction-time-only as-of via learned_at+superseded_by chain-walk); M2 normalize --as-of input to now_iso() format before string comparison; M3 FTS5 index = rebuildable projection with documented rebuild + deterministic alias dedup; M4 measure benefit at memory_selector output (floor 0.42), keep connect/stats contract (contracts.py:233-240) and canary bans (canary_p0_04.py:99-105); M5 write-side population precedes read-layer work; M6 describe tier as transaction-time append log, not bi-temporal; M7 future analytics sidecar = rebuildable read-only projection, no independent writes. Falsification tests T1–T6 (T1 kills the INN-1 filter; T2 validates M1a; T3 lexical ≥30% end-to-end; T4 add-bulk 1,000 edges commits-constant; T5 population gate <50 edges ⇒ NO_INNOVATION_WARRANTED; T6 as-of input robustness). Critical assumptions CA1–CA6 (graph empty, valid-time degenerate, timestamps lexicographic only for producer format, benefit measured end-to-end, FTS5 available sqlite 3.53.4, supersession chains short/acyclic but unasserted).\n26: - Issue-163 SYNTHESIS round 1 accepted (artifact `research/issue-163/synthesis.json`, harness repo, 150 lines): selected design = corrected, re-sequenced temporal+lexical query layer over graph.sqlite. Sequence 0–9: (0) pre-flight G4 check — graph source registered in memory_selector.DEFAULT_SOURCES; (1) M1a one-line write fix `UPDATE edges SET status='superseded', superseded_by=?, valid_until=? WHERE id=?` at graph_memory.py:206-208 (valid_until = same now_iso() as the supeLine truncated
+{"type":"tool_use","timestamp":1788986531024,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"memory","callID":"call_f769394bdc5b44d6b8ecc7b9","state":{"status":"completed","input":{"operation":"search","query":"OUTWARD stage protocol O-IDs receipts issue-263 exemplar"},"output":"Found 10 matches (BM25-ranked, best first).\nA hit here is authoritative — use it even if a parallel/sibling query returned nothing.\nIf you need the FULL body (snippets are truncated), Read the path.\nIf you need an EXACT literal (a connection string, port, token, full command line, path) and the snippet/body only paraphrases or partially shows it, the curated memory may have dropped the precise form — query the history tool for the original message, which holds it verbatim.\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG/checkpoint.md\nScope: sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG, Type: checkpoint, Score: 28.303\n...Assign <<O>>-<<ids>>, classify, select bounded set, read via webfetch, then write the <<stage>> artifact (matching `research/<<issue>>-<<263>>/<<outward>>.json` format) into `/mnt/workdrive/research-<<stage>>/research/<<issue>>-161/` ending with...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c/checkpoint.md\nScope: sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c, Type: checkpoint, Score: 23.068\n...<<OUTWARD>> <<stage>> for process `research-<<263>>-r1` (<<issue>> <<263>>: \"OR3 vertical acceptance: <<OUTWARD>> unified <<stage>> — sqlite WAL + concurrency in Python\"). MUST: real web searches with query/source <<receipts>>, <<O>>-numbered source <<IDs>>...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1/checkpoint.md\nScope: sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1, Type: checkpoint, Score: 17.110\n...memory <<protocol>> over skill loading: the <<stage>> prompt's contract (<<receipts>>, <<O>>-<<IDs>>, no synthesis) matches the established Rune pipeline <<OUTWARD>> <<stage>> exactly, so the DuckDuckGo-HTML-SERP technique and <<issue>>-161...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f782475a4ffegE8Ix6aZJ/checkpoint.md\nScope: sessions/ses_-ffe5f782475a4ffegE8Ix6aZJ, Type: checkpoint, Score: 16.898\n...headless Rune research-pipeline <<OUTWARD>> <<stage>> dispatch for <<issue>>-311. Objective: discover and classify candidate external sources — <<issue>> real searches/discovery calls, preserve query/tool <<receipts>>, assign stable source <<IDs>> (O1, O2...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR/checkpoint.md\nScope: sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR, Type: checkpoint, Score: 15.867\n...reads already executed (<<receipts>> are in `/mnt/workdrive/issue161-harness/research/<<issue>>-310/<<stage>>_<<OUTWARD>>.events.jsonl`). Evidence requirement for the subquestion is already satisfied (see §7); per <<protocol>> \"Continue into further...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1/checkpoint-outward-discovery.md\nScope: sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1, Type: checkpoint, Score: 15.196\n...this is a Rune research pipeline headless <<stage>> dispatch (unified 7-<<stage>> pipeline; <<OUTWARD>> = discovery + reading merged, <<O>>-numbered <<IDs>>, artifact ends `StageCompleted: <<OUTWARD>>`).\n- REQUIRED SOURCE CLASSES (from the dispatch): repo, external.\n\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f826d4b3affeptScH2iSt/checkpoint-handoff-research-loop.md\nScope: sessions/ses_-ffe5f826d4b3affeptScH2iSt, Type: checkpoint, Score: 14.087\n...agent_<<stage>>.<<outward>>_valid (receipt-level) + T6 artifact-level\n- §10 <<receipts>> from event stream, NEVER model self-report → SHIPPED #222 (build_receipt)\n- §11 INNOVATION candidates must derive_from evidence <<IDs>>; ≥1 candidate...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD/checkpoint.md\nScope: sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD, Type: checkpoint, Score: 13.693\n...Rollback: /usr/local/bin/gitea-1.27.2.bak.\n- research/<<issue>>-161/ + <<issue>>-163/ + <<issue>>-<<263>>/ artifact dirs — historical evidence, preserve. #161 legacy ledger render preview at /tmp/ledger161/<<outward>>.json.\n- Pi...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7c9d2281ffessfv3vUH4/checkpoint.md\nScope: sessions/ses_-ffe5f7c9d2281ffessfv3vUH4, Type: checkpoint, Score: 13.405\n...Items here are candidates for promotion to projects/<pid>/MEMORY.md if they prove durable._\n\n- <<Issue>>-161 round uses the newer pipeline shape: unified <<OUTWARD>> (<<O>>-numbered sources) + APPLICABILITY <<stage>> producing `applicability...\n\n### /home/nick/.local/share/mimocode/memory/projects/global/MEMORY-discovered-pipeline-build-history-2026-09-09.md\nScope: projects/global, Type: memory, Score: 13.183\n...deterministic receipt reconciliation — Line truncated
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+{"type":"tool_use","timestamp":1788986537431,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"read","callID":"call_aed0b93291bc467d966d0bc2","state":{"status":"completed","input":{"file_path":"/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md"},"output":"<path>/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md</path>\n<type>file</type>\n<content>\n1: # Memory spillover: pipeline history & completed early-stage artifacts\n2: _Extracted from MEMORY.md ## Discovered durable knowledge (token-budget extraction). Historical/completed content: pipeline conventions, stage techniques, grounding facts, and per-stage artifacts for issue-262 / issue-161 / issue-163 up through INNOVATION. Consult when working older rounds or needing source-level detail; the operative issue-163 constraints (ADVERSARIAL M1–M7/T1–T6, SYNTHESIS round-1, QUALIFY) remain in MEMORY.md._\n3: \n4: ## Entries\n5: \n6: - Rune research pipeline has 8 stages: DEFINE → INWARD → OUTWARD_DISCOVERY → OUTWARD_READING → ADVERSARIAL → INNOVATION → SYNTHESIS (+1 completion/validation stage). Dispatched headless via `.gitea/workflows/research-stage-headless.yml` (PRs #217/#218) + `run_agent_stage.py` (#222).\n7: - Research questions are filed in the Rune repo as `research/issue-<n>-research.md` (or under `/mnt/workdrive/rune/research/<topic>/` subdirectories). DEFINE-stage dispatches may reference \"the research question\" without restating it — locate the question file before classifying.\n8: - Stage-execution tree for research rounds lives at `/mnt/workdrive/research-stage/` (holds src/rune/ + research-executor commits, e.g. HEAD 83ea89c \"OUTWARD_DISCOVERY executor\"); distinct from the subject repo `/mnt/workdrive/rune/`.\n9: - OUTWARD_DISCOVERY technique that works here: plain webfetch of `https://duckduckgo.com/html/?q=<url-encoded query>` returns title+URL+snippet SERPs; batch ≥4 queries in parallel; snippet-level evidence satisfies the \"discover URLs, classify sources, don't read full sources\" stage contract.\n10: - OUTWARD_READING technique that works here: batch webfetch in parallel; GitHub repos read cleaner via `raw.githubusercontent.com/<owner>/<repo>/<branch>/README.md` (avoids page chrome); dev.to and sqliteforum.com (Substack-style) pages fetch OK but carry navigation noise around mid-page content; extracted claims go in a session spillover file (e.g. `checkpoint-outward-reading-sources.md`) with S-numbered source IDs so the ADVERSARIAL stage can reference claims.\n11: - Rune's SQLite usage (grounding for DB-related research questions): ~15 modules in src/rune/ each open fresh short-lived sqlite3 connections per call against a shared STORE_DB (mix of RW and `file:...?mode=ro` URI reads) across multiple OS processes; only task_gate.py sets `PRAGMA journal_mode=WAL` explicitly; sqlite-vec extension must be loaded per connection (issue #26 defect fix).\n12: - Newer pipeline runs use a 7-stage pipeline with a UNIFIED OUTWARD stage (discovery + reading merged, O-numbered source IDs, artifact ends `StageCompleted: OUTWARD`); the older 8-stage split (OUTWARD_DISCOVERY → OUTWARD_READING, S-numbered IDs) still applies to older rounds like issue-262. Deterministic DEFINE contracts may mark sub-stages \"skipped\" while the unified stage still requires \"≥2 unique URLs\".\n13: - Rune's memory stack (grounding for issue-161 OUTWARD): sqlite-vec (dense vectors) + FTS5 (BM25) in one SQLite file (`src/rune/memory_store.py`), hybrid recall accelerated by a precomputed association graph (hops=1); separate headless SQLite graph tier at `memory/graph/graph.sqlite` (`src/rune/graph_memory.py`); no Qdrant dependency exists — the \"vs Qdrant vs graph backends\" part of the question is comparative research, not existing code.\n14: - Issue-262 round already researched SQLite WAL + concurrency (artifact at `research/issue-262/outward.json` + `.firecrawl/` source snapshots); don't re-research WAL in memory-backend rounds.\n15: - Issue-161 round 1 (memory backend abstraction + comparative benchmark harness): ADVERSARIAL settled SURVIVES_WITH_MITIGATIONS. Survivors: sqlite-hybrid-retrieval, retrieval-quality-metrics-suite, reproducibility-contract, matched-precision-comparison-methodology, candidate-pool-vs-ranking-diagnostic, substrate-family-comparative-eval. memory-adapter-protocol REJECTED as duplicate authority — memory_selector.py's source registry (add_source()/DEFAULT_SOURCES, memory_selector.py:130-133 & 504-511, contract `(query, types, budget, min_score) -> list[dict]`) already IS the backend abstraction; do NOT resurrect it (mitigation M5). SYNTHESIS must carry mitigations M1–M10 and convert falsification tests FT1–FT7 into invariants/tests (full text in the SYNTHESIS dispatch and stage artifacts at `/mnt/workdrive/research-stage/research/issue-161/`; expected artifact `researLine truncated
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+{"type":"text","timestamp":1788986553677,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e87041002fASaklhmu","messageID":"msg_g001a087e838ae001WWkZOyLBR","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"Grounding established: this is the Rune research pipeline's unified OUTWARD stage for issue #162 (Qdrant spike), same protocol as issue-161/311/313 — real searches with receipts, O-numbered sources, evidence claims, no synthesis, artifact ending `StageCompleted: OUTWARD`. Let me check the stage state in the harness repo and the issue itself.","time":{"start":1788986552385,"end":1788986553673}}}
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\\u22652 unique URLs for OUTWARD (if required)\",\n          \"expected_artifact\": \"synthesis.json\",\n          \"ambiguous\": false,\n          \"needs_mimo\": false,\n          \"source\": \"deterministic\"\n        },\n        \"mimo_needed\": false\n      },\n      \"deterministic\": true,\n      \"claims\": [\n        {\n          \"id\": \"I1\",\n          \"claim\": \"Relevant file: src/rune/memory_store.py\",\n          \"evidence\": [\n            \"src/rune/memory_store.py\"\n          ],\n          \"status\": \"CURRENT\"\n        },\n        {\n          \"id\": \"I2\",\n          \"claim\": \"Relevant file: src/rune/sleep_time.py\",\n          \"evidence\": [\n            \"src/rune/sleep_time.py\"\n          ],\n          \"status\": \"CURRENT\"\n        },\n        {\n          \"id\": \"I3\",\n          \"claim\": \"Relevant file: src/rune/canary_p1_07.py\",\n          \"evidence\": [\n            \"src/rune/canary_p1_07.py\"\n          ],\n          \"status\": \"CURRENT\"\n        },\n        {\n          \"id\": \"I4\",\n          \"claim\": \"Relevant file: src/rune/curator.py\",\n          \"evidence\": [\n            \"src/rune/curator.py\"\n          ],\n          \"status\": \"CURRENT\"\n        },\n        {\n      Line truncated
+{"type":"tool_use","timestamp":1788986561859,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"bash","callID":"call_26cf80e213d94b749d99c95c","state":{"status":"completed","input":{"command":"tail -5 /mnt/workdrive/issue161-harness/research/issue-162/stage_OUTWARD.events.jsonl 2>/dev/null; wc -l /mnt/workdrive/issue161-harness/research/issue-162/stage_OUTWARD.events.jsonl","description":"Check event log for prior OUTWARD attempts"},"output":"{\"type\":\"text\",\"timestamp\":1788986553677,\"sessionID\":\"ses_-ffe5f78183255ffeT8vvlzqHA\",\"part\":{\"id\":\"prt_g001a087e87041002fASaklhmu\",\"messageID\":\"msg_g001a087e838ae001WWkZOyLBR\",\"sessionID\":\"ses_-ffe5f78183255ffeT8vvlzqHA\",\"type\":\"text\",\"text\":\"Grounding established: this is the Rune research pipeline's unified OUTWARD stage for issue #162 (Qdrant spike), same protocol as issue-161/311/313 — real searches with receipts, O-numbered sources, evidence claims, no synthesis, artifact ending `StageCompleted: OUTWARD`. Let me check the stage state in the harness repo and the issue itself.\",\"time\":{\"start\":1788986552385,\"end\":1788986553673}}}\n{\"type\":\"tool_use\",\"timestamp\":1788986553981,\"sessionID\":\"ses_-ffe5f78183255ffeT8vvlzqHA\",\"part\":{\"type\":\"tool\",\"tool\":\"bash\",\"callID\":\"call_4ed31c5890cc4395b6e65af7\",\"state\":{\"status\":\"completed\",\"input\":{\"command\":\"ls /mnt/workdrive/issue161-harness/research/issue-162/ 2>/dev/null; cat /mnt/workdrive/issue161-harness/research/issue-162/task_tree.json 2>/dev/null | head -60\",\"description\":\"Check issue-162 research stage state\"},\"output\":\"stage_OUTWARD.events.jsonl\\nstage_OUTWARD.mimo.err.log\\ntask_tree.json\\ntelemetry\\n{\\n  \\\"issue\\\": 162,\\n  \\\"round\\\": 1,\\n  \\\"current_stage\\\": \\\"OUTWARD\\\",\\n  \\\"completed_stages\\\": [\\n    \\\"ISSUE\\\",\\n    \\\"INWARD\\\"\\n  ],\\n  \\\"artifacts\\\": {\\n    \\\"ISSUE\\\": {\\n      \\\"contract\\\": {\\n        \\\"issue\\\": 162,\\n        \\\"title\\\": \\\"Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)\\\",\\n        \\\"question_type\\\": \\\"mixed\\\",\\n        \\\"sub_questions\\\": [\\n          \\\"Address: Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)\\\"\\n        ],\\n        \\\"required_stages\\\": [\\n          \\\"ISSUE\\\",\\n          \\\"INWARD\\\",\\n          \\\"OUTWARD\\\",\\n          \\\"ADVERSARIAL\\\",\\n          \\\"INNOVATION\\\",\\n          \\\"SYNTHESIS\\\",\\n          \\\"QUALIFY\\\"\\n        ],\\n        \\\"skipped_stages\\\": {\\n          \\\"APPLICABILITY\\\": \\\"No OUTWARD research to ground against Rune.\\\"\\n        },\\n        \\\"evidence_classes\\\": [\\n          \\\"repo\\\",\\n          \\\"external\\\"\\n        ],\\n        \\\"sufficient_evidence\\\": \\\"\\\\u22652 code-path citations for INWARD; \\\\u22652 unique URLs for OUTWARD (if required)\\\",\\n        \\\"expected_artifact\\\": \\\"synthesis.json\\\",\\n        \\\"ambiguous\\\": false,\\n        \\\"needs_mimo\\\": false,\\n        \\\"source\\\": \\\"deterministic\\\"\\n      },\\n      \\\"deterministic\\\": true\\n    },\\n    \\\"INWARD\\\": {\\n      \\\"context\\\": {\\n        \\\"keywords\\\": [\\n          \\\"qdrant\\\",\\n          \\\"associative\\\",\\n          \\\"memory\\\",\\n          \\\"projection\\\",\\n          \\\"spike\\\",\\n          \\\"dense\\\",\\n          \\\"sparse\\\",\\n          \\\"multivector\\\",\\n          \\\"colbert\\\",\\n          \\\"late\\\",\\n          \\\"interaction\\\",\\n          \\\"reranking\\\",\\n          \\\"plain\\\",\\n          \\\"summary\\\",\\n          \\\"architecture_frontier_handoff\\\",\\n          \\\"highest\\\",\\n\",\"metadata\":{\"output\":\"stage_OUTWARD.events.jsonl\\nstage_OUTWARD.mimo.err.log\\ntask_tree.json\\ntelemetry\\n{\\n  \\\"issue\\\": 162,\\n  \\\"round\\\": 1,\\n  \\\"current_stage\\\": \\\"OUTWARD\\\",\\n  \\\"completed_stages\\\": [\\n    \\\"ISSUE\\\",\\n    \\\"INWARD\\\"\\n  ],\\n  \\\"artifacts\\\": {\\n    \\\"ISSUE\\\": {\\n      \\\"contract\\\": {\\n        \\\"issue\\\": 162,\\n        \\\"title\\\": \\\"Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)\\\",\\n        \\\"question_type\\\": \\\"mixed\\\",\\n        \\\"sub_questions\\\": [\\n          \\\"Address: Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)\\\"\\n        ],\\n        \\\"required_stages\\\": [\\n          \\\"ISSUE\\\",\\n          \\\"INWARD\\\",\\n          \\\"OUTWARD\\\",\\n          \\\"ADVERSARIAL\\\",\\n          \\\"INNOVATION\\\",\\n          \\\"SYNTHESIS\\\",\\n          \\\"QUALIFY\\\"\\n        ],\\n        \\\"skipped_stages\\\": {\\n          \\\"APPLICABILITY\\\": \\\"No OUTWARD research to ground against Rune.\\\"\\n        },\\n   Line truncated
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+{"type":"step_start","timestamp":1788986574759,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e8c7a5001tHqZMpYIC","messageID":"msg_g001a087e8a656001Jne4IAT0n","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"2f8d18331bc031e384acd827f7551a16f1e4b27e","type":"step-start"}}
+{"type":"text","timestamp":1788986577665,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e8c947001w2EDz0FKU","messageID":"msg_g001a087e8a656001Jne4IAT0n","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"The events log only contains this session's activity — no prior external calls exist. I'm the OUTWARD executor; executing discovery now. Plan: (1) repo grounding receipts from the harness repo, (2) batch DuckDuckGo SERP discovery (established technique from prior rounds), (3) classify O-IDs, (4) read a bounded set, (5) extract evidence claims, (6) write `research/issue-162/outward.json`.\n\nFirst: repo-side grounding + first SERP batch in parallel.","time":{"start":1788986575175,"end":1788986577663}}}
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Qdrant\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            qdrant.tech/documentation/fastembed/fastembed-colbert/\n                          \n                          \n                        \n                      \n                    \n\n                    \n                      \n                        Use FastEmbed to generate ColBERT multivectors and index them in Qdrant for late-interaction retrieval and reranking with native multivector support.\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        Multivectors and Late Interaction - Qdrant\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            qdrant.teLine truncated
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Qdrant\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            qdrant.tech/documentation/search/hybrid-queries/\n                          \n                          \n                        \n                      \n                    \n\n                    \n                      \n                        Run hybrid queries in Qdrant: fuse dense, sparse, and multivector results with RRF or DBSF, layer custom scoring with Formula Query, and pick the right method for your data.\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        Hybrid Search - Qdrant\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                     Line truncated
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+{"type":"step_start","timestamp":1788986588148,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e8fbf200162bNIjBBY","messageID":"msg_g001a087e8d6b40015LkEMevAB","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"f0d91d9f5cd8d9fd2b3b97436b1e22595e6850de","type":"step-start"}}
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Qdrant\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            qdrant.tech/documentation/installation/\n                          \n                          \n                        \n                      \n                    \n\n                    \n                      \n                        Install Qdrant via Docker, Kubernetes, or binary releases — review CPU, memory, storage, and networking requirements for self-hosted deployments.\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        Fix Qdrant Docker OOMKilled: Set Memory Limits for Persistent Storage ...\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n               Line truncated
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Covers MaxSim scoring, ColBERTv2 compression, PLAID engine, and production RAG…\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        Reranking: Cross-Encoders, ColBERT, Cohere | Neel Mishra\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                          Line truncated
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charset=UTF-8)","time":{"start":1788986597425,"end":1788986597576}},"id":"prt_g001a087e91e6c001MzcFf17H0","sessLine truncated
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+{"type":"step_start","timestamp":1788986617820,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e96fdb001rqOfVVHjX","messageID":"msg_g001a087e92102001NYiEiBq87","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"1d5d522f72a0bf7554f233daac9ec663392e73c2","type":"step-start"}}
+{"type":"text","timestamp":1788986619492,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e973ed00107IFY3Ai4","messageID":"msg_g001a087e92102001NYiEiBq87","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"4 SERPs succeeded; the 5th hit a DuckDuckGo bot CAPTCHA (receipt preserved — recorded as limitation). Discovery is sufficient: ~20 candidate URLs across 4 query classes. Now classifying and reading a bounded selection — official docs (O1, O9, O16), primary paper (O12), independent vendor-neutral analysis (O11), and community ops ground truth (O17), plus the official repo README (O3) via raw.githubusercontent (established technique).","time":{"start":1788986618861,"end":1788986619489}}}
+{"type":"tool_use","timestamp":1788986619586,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_479c213bee2e4463b2a3c341","state":{"status":"completed","input":{"format":"text","url":"https://arxiv.org/abs/2004.12832"},"output":"[2004.12832] ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT\n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n    \n\n\n\n    Skip to main content\n  \n  \n  \n\n  \n\n  \n    \n  \n\n  \n    \n      \n      \n      \n    \n  \n\n  \n      \n        \n        \n      \n      Search\n    \n    Submit\n    Donate\n    \n      Log in\n  \n\n\n\n  \n    \n      Search arXiv\n      \n      \n      \n    \n    \n      Press Enter to search &middot; Advanced search\n    \n  \n\n    \n      \n\n\n  \n    \n      Computer Science > Information Retrieval\n    \n\n    \n      arXiv:2004.12832 (cs)\n    \n\n\n  \n    \n  [Submitted on 27 Apr 2020 (v1), last revised 4 Jun 2020 (this version, v2)]\n    Title:ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT\n    Authors:Omar Khattab, Matei Zaharia            View a PDF of the paper titled ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT, by Omar Khattab and Matei Zaharia\n    View PDF\n    HTML (experimental)\n\n\n\n    \n            Abstract:Recent progress in Natural Language Understanding (NLU) is driving fast-paced advances in Information Retrieval (IR), largely owed to fine-tuning deep language models (LMs) for document ranking. While remarkably effective, the ranking models based on these LMs increase computational cost by orders of magnitude over prior approaches, particularly as they must feed each query-document pair through a massive neural network to compute a single relevance score. To tackle this, we present ColBERT, a novel ranking model that adapts deep LMs (in particular, BERT) for efficient retrieval. ColBERT introduces a late interaction architecture that independently encodes the query and the document using BERT and then employs a cheap yet powerful interaction step that models their fine-grained similarity. By delaying and yet retaining this fine-granular interaction, ColBERT can leverage the expressiveness of deep LMs while simultaneously gaining the ability to pre-compute document representations offline, considerably speeding up query processing. Beyond reducing the cost of re-ranking the documents retrieved by a traditional model, ColBERT&#39;s pruning-friendly interaction mechanism enables leveraging vector-similarity indexes for end-to-end retrieval directly from a large document collection. We extensively evaluate ColBERT using two recent passage search datasets. Results show that ColBERT&#39;s effectiveness is competitive with existing BERT-based models (and outperforms every non-BERT baseline), while executing two orders-of-magnitude faster and requiring four orders-of-magnitude fewer FLOPs per query.\n    \n\n    \n    \n              \n          Comments:\n          Accepted at SIGIR 2020\n        \n\n          Subjects:\n          \n            Information Retrieval (cs.IR); Computation and Language (cs.CL)\n        \n          Cite as:\n          arXiv:2004.12832 [cs.IR]\n        \n        \n          &nbsp;\n          (or \n              arXiv:2004.12832v2 [cs.IR] for this version)\n          \n        \n        \n          &nbsp;\n                        https://doi.org/10.48550/arXiv.2004.12832\n              \n                \n                Focus to learn more\n              \n              \n              \n                                  arXiv-issued DOI via DataCite\n            \n          \n        \n    \n  \n\n    \n      Submission history From: Omar Khattab [view email]                  [v1]\n        Mon, 27 Apr 2020 14:21:03 UTC (1,437 KB)\n    [v2]\n        Thu, 4 Jun 2020 05:28:21 UTC (3,959 KB)\n\n  \n  \n    \n      \n      Full-text links:\n      Access Paper:\n      \n  \nView a PDF of the paper titled ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT, by Omar Khattab and Matei ZahariaView PDFHTML (experimental)TeX Source\n \n      view license\n    \n        \n      Additional Features\n      \n        Audio Summary\n      \n    \n    \n    Current browse context:\n  cs.IR\n\n  \n\n      &lt;&nbsp;prev\n    \n    &nbsp; | &nbsp;    \n      next&nbsp;&gt;\n    \n  \n    new\n     | \n    recent\n     | 2020-04\n  \n    Change to browse by:\n    \n        cs\n        cs.CL\n    \n  \n\n    \n      \n        References &amp; Citations\n        \n          NASA ADSGoogle Scholar\n          Semantic Scholar\n        \n        \n      \n\n    \n        \n             1 blog link (what is this?)\n        \n    \n\n    DBLP - CS Bibliography\n    \n      listing | bibtex    \n    \nOmar KhattabMatei Zaharia    \n  \n    export BibTeXLine truncated
+{"type":"tool_use","timestamp":1788986619828,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_fac6be73fc90440aa7e68f48","state":{"status":"completed","input":{"format":"text","url":"https://qdrant.tech/documentation/search/hybrid-queries/"},"output":"Hybrid Queries - Qdrant\nDevelopDeployEcosystemLearnAPI Reference\nSearch\nLog in\nStart Free\n\nSearch\nDevelop\nDeploy\nEcosystem\nLearn\nAPI ReferenceGetting StartedOverviewWhat is Qdrant?Understanding Vector Search in QdrantLocal QuickstartCloud QuickstartUser ManualManage DataPointsVectorsPayloadCollectionsStorageIndexingQuantizationMultitenancyBulk UploadSearchSearchFilteringHybrid QueriesExploreSearch RelevanceLow-Latency SearchText SearchText FilteringFull-Text SearchHybrid SearchInferenceInference APIBM25Cloud InferenceExternal ProvidersMatryoshka ModelsQdrant EdgeEdge APIShard LifecycleConfigurationUpdating DataReading DataSnapshotsQuickstartOn-Device EmbeddingsBM25Data Synchronization PatternsSynchronize with a ServerQdrant Web UIAPI & SDKsQdrant ToolsAgent SkillsFastEmbedQuickstartFastEmbed & QdrantOptimize ThroughputWorking with miniCOILWorking with SPLADEWorking with ColBERTReranking with FastEmbedMulti-Vector PostprocessingQdrant MCP ServerTutorialsOverviewBasicsSemantic Search 101Multimodal SearchHybrid SearchHybrid Search with RerankingSearch EngineeringMultivectors and Late InteractionRelevance Feedback Retrieval in QdrantCollaborative FilteringMultivector Document RetrievalMeasuring ANN RecallMulti-Representation SearchBranch-Aware SearchIndexing Payloads of Random ShapeCompressed Multivector SearchStatic EmbeddingsOperations & ScaleSnapshotsData MigrationMigrate to a New Embedding ModelIncremental Embedding UpdatesPrevent Unoptimized UsageBlue-Green Cluster DeploymentTime-Based ShardingLarge-Scale SearchGPU-Accelerated HNSW IndexingSecure a Self-Hosted Qdrant InstanceDevelop & ImplementAsync APISemantic Search for CodeBuild a Semantic Search APIBuild a Hybrid Search APISupportRelease NotesFAQQdrant FundamentalsDatabase OptimizationGetting StartedOverviewWhat is Qdrant?Understanding Vector Search in QdrantLocal QuickstartCloud QuickstartUser ManualManage DataPointsVectorsPayloadCollectionsStorageIndexingQuantizationMultitenancyBulk UploadSearchSearchFilteringHybrid QueriesExploreSearch RelevanceLow-Latency SearchText SearchText FilteringFull-Text SearchHybrid SearchInferenceInference APIBM25Cloud InferenceExternal ProvidersMatryoshka ModelsQdrant EdgeEdge APIShard LifecycleConfigurationUpdating DataReading DataSnapshotsQuickstartOn-Device EmbeddingsBM25Data Synchronization PatternsSynchronize with a ServerQdrant Web UIAPI & SDKsQdrant ToolsAgent SkillsFastEmbedQuickstartFastEmbed & QdrantOptimize ThroughputWorking with miniCOILWorking with SPLADEWorking with ColBERTReranking with FastEmbedMulti-Vector PostprocessingQdrant MCP ServerTutorialsOverviewBasicsSemantic Search 101Multimodal SearchHybrid SearchHybrid Search with RerankingSearch EngineeringMultivectors and Late InteractionRelevance Feedback Retrieval in QdrantCollaborative FilteringMultivector Document RetrievalMeasuring ANN RecallMulti-Representation SearchBranch-Aware SearchIndexing Payloads of Random ShapeCompressed Multivector SearchStatic EmbeddingsOperations & ScaleSnapshotsData MigrationMigrate to a New Embedding ModelIncremental Embedding UpdatesPrevent Unoptimized UsageBlue-Green Cluster DeploymentTime-Based ShardingLarge-Scale SearchGPU-Accelerated HNSW IndexingSecure a Self-Hosted Qdrant InstanceDevelop & ImplementAsync APISemantic Search for CodeBuild a Semantic Search APIBuild a Hybrid Search APISupportRelease NotesFAQQdrant FundamentalsDatabase OptimizationDocumentationSearchHybrid QueriesHybrid and Multi-Stage QueriesAvailable as of v1.10.0With the introduction of multiple named vectors per point, there are use-cases when the best search is obtained by combining multiple queries,\nor by performing the search in more than one stage.Qdrant has a flexible and universal interface to make this possible, called Query API (API reference).The main component for making the combinations of queries possible is the prefetch parameter, which enables making sub-requests.Specifically, whenever a query has at least one prefetch, Qdrant will:Perform the prefetch query (or queries),Apply the main query over the results of its prefetch(es).Additionally, prefetches can have prefetches themselves, so you can have nested prefetches.Using offset parameter only affects the main query. This means that the prefetches must have a limit of at least limit + offset of the main query, otherwise you can get an empty result.Hybrid SearchOne of the most common problems when you have different representations of the same data is to combine the queried points for each representation into a single result.Fusing results from multiple queriesFor example, in text search, it is often useful to combine dense and sparse vectors to get the best of both worlds: sLine truncated
+{"type":"tool_use","timestamp":1788986619831,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_f3be5019786847d18ac8d1db","state":{"status":"completed","input":{"format":"text","url":"https://qdrant.tech/documentation/tutorials-search-engineering/using-multivector-representations/"},"output":"Multivectors and Late Interaction - Qdrant\nDevelopDeployEcosystemLearnAPI Reference\nSearch\nLog in\nStart Free\n\nSearch\nDevelop\nDeploy\nEcosystem\nLearn\nAPI ReferenceGetting StartedOverviewWhat is Qdrant?Understanding Vector Search in QdrantLocal QuickstartCloud QuickstartUser ManualManage DataPointsVectorsPayloadCollectionsStorageIndexingQuantizationMultitenancyBulk UploadSearchSearchFilteringHybrid QueriesExploreSearch RelevanceLow-Latency SearchText SearchText FilteringFull-Text SearchHybrid SearchInferenceInference APIBM25Cloud InferenceExternal ProvidersMatryoshka ModelsQdrant EdgeEdge APIShard LifecycleConfigurationUpdating DataReading DataSnapshotsQuickstartOn-Device EmbeddingsBM25Data Synchronization PatternsSynchronize with a ServerQdrant Web UIAPI & SDKsQdrant ToolsAgent SkillsFastEmbedQuickstartFastEmbed & QdrantOptimize ThroughputWorking with miniCOILWorking with SPLADEWorking with ColBERTReranking with FastEmbedMulti-Vector PostprocessingQdrant MCP ServerTutorialsOverviewBasicsSemantic Search 101Multimodal SearchHybrid SearchHybrid Search with RerankingSearch EngineeringMultivectors and Late InteractionRelevance Feedback Retrieval in QdrantCollaborative FilteringMultivector Document RetrievalMeasuring ANN RecallMulti-Representation SearchBranch-Aware SearchIndexing Payloads of Random ShapeCompressed Multivector SearchStatic EmbeddingsOperations & ScaleSnapshotsData MigrationMigrate to a New Embedding ModelIncremental Embedding UpdatesPrevent Unoptimized UsageBlue-Green Cluster DeploymentTime-Based ShardingLarge-Scale SearchGPU-Accelerated HNSW IndexingSecure a Self-Hosted Qdrant InstanceDevelop & ImplementAsync APISemantic Search for CodeBuild a Semantic Search APIBuild a Hybrid Search APISupportRelease NotesFAQQdrant FundamentalsDatabase OptimizationGetting StartedOverviewWhat is Qdrant?Understanding Vector Search in QdrantLocal QuickstartCloud QuickstartUser ManualManage DataPointsVectorsPayloadCollectionsStorageIndexingQuantizationMultitenancyBulk UploadSearchSearchFilteringHybrid QueriesExploreSearch RelevanceLow-Latency SearchText SearchText FilteringFull-Text SearchHybrid SearchInferenceInference APIBM25Cloud InferenceExternal ProvidersMatryoshka ModelsQdrant EdgeEdge APIShard LifecycleConfigurationUpdating DataReading DataSnapshotsQuickstartOn-Device EmbeddingsBM25Data Synchronization PatternsSynchronize with a ServerQdrant Web UIAPI & SDKsQdrant ToolsAgent SkillsFastEmbedQuickstartFastEmbed & QdrantOptimize ThroughputWorking with miniCOILWorking with SPLADEWorking with ColBERTReranking with FastEmbedMulti-Vector PostprocessingQdrant MCP ServerTutorialsOverviewBasicsSemantic Search 101Multimodal SearchHybrid SearchHybrid Search with RerankingSearch EngineeringMultivectors and Late InteractionRelevance Feedback Retrieval in QdrantCollaborative FilteringMultivector Document RetrievalMeasuring ANN RecallMulti-Representation SearchBranch-Aware SearchIndexing Payloads of Random ShapeCompressed Multivector SearchStatic EmbeddingsOperations & ScaleSnapshotsData MigrationMigrate to a New Embedding ModelIncremental Embedding UpdatesPrevent Unoptimized UsageBlue-Green Cluster DeploymentTime-Based ShardingLarge-Scale SearchGPU-Accelerated HNSW IndexingSecure a Self-Hosted Qdrant InstanceDevelop & ImplementAsync APISemantic Search for CodeBuild a Semantic Search APIBuild a Hybrid Search APISupportRelease NotesFAQQdrant FundamentalsDatabase OptimizationDocumentationSearch EngineeringMultivectors and Late InteractionMultivector Representations for Reranking in QdrantTime: 30 minLevel: IntermediateMultivector Representations are one of the most powerful features of Qdrant. However, most people don&rsquo;t use them effectively, resulting in massive RAM overhead, slow inserts, and wasted compute.In this tutorial, you&rsquo;ll discover how to effectively use multivector representations in Qdrant.What are Multivector Representations?In most vector engines, each document is represented by a single vector - an approach that works well for short texts but often struggles with longer documents. Single vector representations perform pooling of the token-level embeddings, which obviously leads to losing some information.Multivector representations offer a more fine-grained alternative where a single document is represented using multiple vectors, often at the token or phrase level. This enables more precise matching between specific query terms and relevant parts of the document. Matching is especially effective in Late Interaction models like ColBERT, which retain token-level embeddings and perform interaction during query time leading to relevance scoring.As you willLine truncated
+{"type":"tool_use","timestamp":1788986621747,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_db19d2f4243a4984b5483a72","state":{"status":"completed","input":{"format":"text","url":"https://weaviate.io/blog/late-interaction-overview"},"output":"An Overview of Late Interaction Retrieval Models: ColBERT, ColPali, and ColQwen | Weaviate\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n← Back to BlogsSkip to main contentIntroducing Engram by Weaviate - now GA - Read our Blog Product▼Solutions▼EnterpriseDevelopers▼Company▼PricingContactLog inTry now☰An Overview of Late Interaction Retrieval Models: ColBERT, ColPali, and ColQwenApril 9, 2025 · 21 min readLeonie MonigattiMachine Learning EngineerDanny WilliamsMachine Learning EngineerVictoria SlocumMachine Learning Engineer\n\nWhy Late Interaction?\nLate interaction retrieval models are changing how we find and retrieve information. These models allow for semantically rich interactions that enable a precise retrieval process across different modalities of unstructured data, including text and images. By decomposing query and document embeddings into lower-level representations, late interaction models use multi-vector retrieval and improve both accuracy and scalability compared to no-interaction and full-interaction dense retrieval models.\nLate interaction models can be used across various retrieval tasks, helping researchers and practitioners find relevant documents in large document collections, such as financial documents or legal contracts. These models are particularly helpful in downstream tasks requiring efficient retrieval processes, such as search engines or Generative AI applications, such as Retrieval-Augmented Generation (RAG) pipelines, where semantic precision can improve information extraction and understanding.\n3 Types of Interaction in Dense Retrieval Models\nDense retrieval models can be categorized based on their type of “interaction”. A dense retrieval model is a model that uses some type of neural network architecture to retrieve relevant documents for a search query. In this context, “interaction” refers to the process of assessing how well a document matches a given search query by comparing their representations. This section discusses the different types of interactions in dense retrieval models.\nNo-interaction Retrieval Models\nTraditional methods for retrieval commonly use “no-interaction” retrieval models. In this case, the search query and documents are processed separately:\n\nDuring the indexing phase, one dense vector embedding is precomputed for each document. The document is first split up into separate tokens, all tokens are passed together through a neural network model, typically a transformer model, to obtain separate dense embeddings for each token. Finally, the token embeddings are calculated into a single vector representation via pooling.\nDuring the online querying phase, one vector is computed for the search query to search for similar documents from the pre-computed document embeddings with a similarity metric (e.g., dot product, cosine similarity).\n\nAdvantages of no-interaction retrieval models are primarily that they are fast and computationally efficient. The vector representations of the documents are already pre-computed and indexed offline, and at query time, only the query embeddings have to be computed. This makes this solution scalable for large-scale information retrieval systems and vector search applications.\nDisadvantages of no-interaction retrieval models lie in the lack of interaction between the search query and the documents. Because the search query and the documents are processed separately and compressed into single vector embeddings, this approach can miss contextual nuances. Any contextual nuances shared from one token to another have to be compressed before the comparison takes place - meaning similarity is compared between the whole document and the whole query, rather than on a token-by-token level.\nThese characteristics make no-interaction models great for first-stage retrieval, where candidates are retrieved from a large document collection, like in vector search. Examples of no-interaction retrieval models are bi-encoders, such as OpenAI’s text-embedding-3-small.\n\nFull interaction Retrieval Models\nFull interaction retrieval models process the search query and documents together. That’s why they are sometimes also called early interaction or all-to-all interaction retrieval models. In contrast to no-interaction models, all-to-all interaction models process everything at query time. For this, the query is concatenated with each document, and then they are processed together for full cross-attention.\nAdvantages of full interaction retrieval models stem from them being contextually rich, meaning they effectively capture nuanced contextual relationships between the search query and the document.Line truncated
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+{"type":"tool_use","timestamp":1788986628698,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_45c4fe9e531d4319bd472c18","state":{"status":"completed","input":{"format":"text","url":"https://raw.githubusercontent.com/qdrant/qdrant/master/README.md"},"output":"<p align=\"center\">\n  <picture>\n      <source media=\"(prefers-color-scheme: dark)\" srcset=\"https://github.com/qdrant/qdrant/raw/master/docs/logo-dark.svg\">\n      <source media=\"(prefers-color-scheme: light)\" srcset=\"https://github.com/qdrant/qdrant/raw/master/docs/logo-light.svg\">\n      <img height=\"100\" alt=\"Qdrant\" src=\"https://github.com/qdrant/qdrant/raw/master/docs/logo.svg\">\n  </picture>\n</p>\n\n<p align=\"center\">\n    <b>Vector Search Engine for the next generation of AI applications</b>\n</p>\n\n<p align=center>\n    <a href=\"https://github.com/qdrant/qdrant/actions/workflows/rust.yml\"><img src=\"https://img.shields.io/github/actions/workflow/status/qdrant/qdrant/rust.yml?style=flat-square\" alt=\"Tests status\"></a>\n    <a href=\"https://api.qdrant.tech/\"><img src=\"https://img.shields.io/badge/Docs-OpenAPI%203.0-success?style=flat-square\" alt=\"OpenAPI Docs\"></a>\n    <a href=\"https://github.com/qdrant/qdrant/blob/master/LICENSE\"><img src=\"https://img.shields.io/github/license/qdrant/qdrant?style=flat-square\" alt=\"Apache 2.0 License\"></a>\n    <a href=\"https://qdrant.to/discord\"><img src=\"https://img.shields.io/discord/907569970500743200?logo=Discord&style=flat-square&color=7289da\" alt=\"Discord\"></a>\n    <a href=\"https://qdrant.to/roadmap\"><img src=\"https://img.shields.io/badge/Roadmap-2025-bc1439.svg?style=flat-square\" alt=\"Roadmap 2025\"></a>\n    <a href=\"https://cloud.qdrant.io/\"><img src=\"https://img.shields.io/badge/Qdrant-Cloud-24386C.svg?logo=cloud&style=flat-square\" alt=\"Qdrant Cloud\"></a>\n</p>\n\n**Qdrant** (read: _quadrant_) is a vector similarity search engine and vector database.\nIt provides a production-ready service with a convenient API to store, search, and manage points—vectors with an additional payload.\nQdrant is tailored for extended filtering support, making it useful for all sorts of neural-network or semantic-based matching, faceted search, and other applications.\n\nQdrant is written in Rust 🦀, which makes it fast and reliable even under high load. See [benchmarks](https://qdrant.tech/benchmarks/).\n\nWith Qdrant, embeddings or neural network encoders can be turned into full-fledged applications for matching, searching, recommending, and much more!\n\nQdrant is also available as a fully managed **[Qdrant Cloud](https://cloud.qdrant.io/)** ⛅ including a **free tier**.\n\n<p align=\"center\">\n<strong><a href=\"https://qdrant.tech/documentation/quickstart/\">Quick Start</a> • <a href=\"#agent-skills\">Agent Skills</a> • <a href=\"#clients\">Client Libraries</a> • <a href=\"#demo-projects\">Demo Projects</a> • <a href=\"#integrations\">Integrations</a> • <a href=\"#contacts\">Contact</a>\n\n</strong>\n</p>\n\n## Getting Started\n\n### Agent Skills\n\nQdrant provides a collection of ready-to-use [agent skills](https://github.com/qdrant/skills) that bring Qdrant's vector search capabilities directly into your AI coding assistant. Install these skills to empower your agent in making critical engineering decisions for optimal vector search performance, such as quantization, sharding, tenant isolation, hybrid search, model migration, and more.\n\n### Client-Server\n\nTo experience the full power of Qdrant locally, run the container with this command:\n\n```bash\ndocker run -p 6333:6333 qdrant/qdrant\n```\n\nNote that this starts an insecure deployment without authentication, open to all network interfaces. Please refer to [secure your instance](https://qdrant.tech/documentation/security/#secure-your-instance).\n\nNow you can connect to the server with any [client](#clients). For example, using Python:\n\n```python\nfrom qdrant_client import QdrantClient\n\nclient = QdrantClient(url=\"http://localhost:6333\")\n```\n\nBefore deploying Qdrant to production, be sure to read our [installation](https://qdrant.tech/documentation/installation/) and [security](https://qdrant.tech/documentation/security/) guides.\n\n### Clients\n\nQdrant offers the following client libraries to help you integrate it into your application stack:\n\n- Official:\n  - [Go client](https://github.com/qdrant/go-client)\n  - [Rust client](https://github.com/qdrant/rust-client)\n  - [JavaScript/TypeScript client](https://github.com/qdrant/qdrant-js)\n  - [Python client](https://github.com/qdrant/qdrant-client)\n  - [.NET/C# client](https://github.com/qdrant/qdrant-dotnet)\n  - [Java client](https://github.com/qdrant/java-client)\n- Community:\n  - [Kotlin](https://github.com/NaCode-Studios/Kdrant)\n  - [PHP](https://github.com/hkulekci/qdrant-php)\n\n### Qdrant Edge\n\n[Qdrant Edge](https://qdrant.tech/documentation/edge/) is a lightweightLine truncated
+{"type":"tool_use","timestamp":1788986628934,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"webfetch","callID":"call_834ef51273c94e19a2f60439","state":{"status":"completed","input":{"format":"text","url":"https://github.com/qdrant/qdrant/blob/master/README.md"},"output":"qdrant/README.md at master · qdrant/qdrant · GitHub\n\n\n\n  \n  \n  \n  \n\n    \n  \n\n\n  \n\n\n    \n\n\n  \n  \n\n  \n  \n\n    \n\n\n\n\n\n\n\n  \n\n  \n\n\n\n\n    \n\n  \n\n    \n\n    \n\n      \n\n      \n\n    \n    \n    \n\n      \n  \n  \n\n\n\n\n      \n\n\n\n        \n\n\n  \n  \n  \n  \n\n  \n\n      \n\n    \n\n  \n\n  \n  \n\n\n\n    \n\n    \n  \n\n\n  \n\n\n  \n\n  \n  \n\n  \n  \n  \n\n\n\n\n\n  \n\n  \n\n  \n    \n      \n      \n\n    \n      Skip to content\n\n      \n    \n      \n      \n\n\n\n\n\n  \n  \n\n\n\n\n\n\n      \n\n          \n\n                \n\n\n\n\n\n\n\n\n\n\n\n\n\n  \n  Navigation MenuSign inAppearance settingsPlatformAI CODE CREATIONGitHub CopilotWrite better code with AIGitHub Copilot appDirect agents from issue to mergeMCP RegistryIntegrate external toolsDEVELOPER WORKFLOWSActionsAutomate any workflowCodespacesInstant dev environmentsIssuesPlan and track workCode ReviewManage code changesCode QualityEnforce quality at mergeAPPLICATION SECURITYGitHub Advanced SecurityFind and fix vulnerabilitiesCode securitySecure your code as you buildSecret protectionStop leaks before they startEXPLOREWhy GitHubDocumentationBlogChangelogMarketplaceView all featuresSolutionsBY COMPANY SIZEEnterprisesSmall and medium teamsStartupsNonprofitsBY USE CASEApp ModernizationDevSecOpsDevOpsCI/CDView all use casesBY INDUSTRYHealthcareFinancial servicesManufacturingGovernmentView all industriesView all solutionsResourcesEXPLORE BY TOPICAISoftware DevelopmentDevOpsSecurityView all topicsEXPLORE BY TYPECustomer storiesEvents &amp; webinarsEbooks &amp; reportsBusiness insightsGitHub SkillsSUPPORT &amp; SERVICESDocumentationCustomer supportCommunity forumTrust centerPartnersView all resourcesOpen SourceCOMMUNITYGitHub SponsorsFund open source developersPROGRAMSSecurity LabMaintainer CommunityGitHub StarsArchive ProgramREPOSITORIESTopicsTrendingCollectionsEnterpriseENTERPRISE SOLUTIONSEnterprise platformAI-powered developer platformAVAILABLE ADD-ONSGitHub Advanced SecurityEnterprise-grade security featuresCopilot for BusinessEnterprise-grade AI featuresPremium SupportEnterprise-grade 24/7 supportPricingSearch/Sign inSign upAppearance settings\n\n\n\n\n      \n  \n        \n    \n\n        You signed in with another tab or window. Reload to refresh your session.\n        You signed out in another tab or window. Reload to refresh your session.\n        You switched accounts on another tab or window. Reload to refresh your session.\n\n      \n    \n\nDismiss alert\n\n\n  \n\n    \n\n  \n\n\n\n\n\n\n\n\n    \n\n\n\n\n\n  \n    \n\n  \n    \n      \n    \n\n    \n    \n      \n      {{ message }}\n\n    \n  \n\n  \n\n\n\n    \n\n\n\n\n\n\n  \n        \n    \n      \n      \n    \n\n      \n  \n  \n    \n  \n    \n      \n\n              Uh oh!\n\n              There was an error while loading. Please reload this page.\n\n\n  \n  \n\n\n    \n\n\n\n\n\n\n\n\n  \n\n  \n\n      \n\n        \n            \n  \n      \n    \n\n    \n    \n      \n        qdrant\n    \n    /\n    \n      qdrant\n    \n\n    Public\n  \n\n\n        \n\n        \n            \n    \n      \n\n  \n                \n    \nNotifications\n    You must be signed in to change notification settings\n\n  \n\n  \n              \n    \nFork\n    2.7k\n\n  \n\n  \n        \n            \n    \n\n          Star\n          34.5k\n\n  \n\n\n\n        \n      \n\n        \n\n\n\n          \n\n  \n      \n  \n    \n              \n    \n\n        Code\n          \n\n\n    \n\n      \n  \n    \n              \n    \n\n        Issues\n          495\n\n\n    \n\n      \n  \n    \n              \n    \n\n        Pull requests\n          208\n\n\n    \n\n      \n  \n    \n              \n    \n\n        Discussions\n          \n\n\n    \n\n      \n  \n    \n              \n    \n\n        Actions\n          \n\n\n    \n\n      \n  \n    \n              \n    \n\n        Projects\n          \n\n\n    \n\n      \n  \n    \n              \n    \n\n        Security and quality\n          1\n\n\n    \n\n      \n  \n    \n              \n    \n\n        Insights\n          \n\n\n    \n\n\n          \n  \n      \n    \n\nAdditional navigation options\n\n\n\n  \n    \n                \n  \n    \n        \n    \n    \n    \n        \n          \n    \n\n        \n      \n        \n          Code\n      \n\n  \n\n        \n    \n    \n    \n        \n          \n    \n\n        \n      \n        \n          Issues\n      \n\n  \n\n        \n    \n    \n    \n        \n          \n    \n\n        \n      \n        \n          Pull requests\n      \n\n  \n\n        \n    \n    \n    \n        \n          \n    \n\n        \n      \n        \n          DiscLine truncated
+{"type":"step_finish","timestamp":1788986628957,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087e99b46001nJM0U5d36","reason":"tool-calls","snapshot":"9a70c0f2f153f2dd1070e927e4010d2991c72850","messageID":"msg_g001a087e97f7a0010EXFLwCm0","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":74831,"input":55697,"output":62,"reasoning":0,"cache":{"write":0,"read":19072}},"cost":0}}
+{"type":"step_start","timestamp":1788986678828,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ea5e2a001wOU0eTzOC","messageID":"msg_g001a087e99b91001xdHu0A7Eo","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"eb6236fc29714f4c7fcb940c89c0fe76279d3733","type":"step-start"}}
+{"type":"text","timestamp":1788986768050,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ea69e8002Q5rqRAFRQ","messageID":"msg_g001a087e99b91001xdHu0A7Eo","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"Both reads succeeded — and the README surfaced a directly relevant discovery: **Qdrant Edge**, an in-process embedded variant (Rune is embedded/local-first). Evidence requirement is now well satisfied (6 sources read across official docs, official repo, primary paper, and independent analysis). Per the stage contract (\"do NOT continue into further research after the evidence requirement is satisfied\"), I'm stopping discovery/reading and writing the stage artifact.","time":{"start":1788986681832,"end":1788986768044}}}
+{"type":"tool_use","timestamp":1788986768056,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"write","callID":"call_c2b18fadc0774abea31bd900","state":{"status":"completed","input":{"content":"{\n  \"stage\": \"OUTWARD\",\n  \"issue\": 162,\n  \"round\": 1,\n  \"generated_by\": \"MiMoCode headless stage dispatch\",\n  \"subquestion\": {\n    \"address\": \"Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)\"\n  },\n  \"required_source_classes\": [\"repo\", \"external\"],\n  \"discovery\": {\n    \"queries\": [\n      {\n        \"id\": \"Q1\",\n        \"tool\": \"webfetch\",\n        \"url\": \"https://duckduckgo.com/html/?q=qdrant+dense+sparse+multivector+vectors+hybrid+search+documentation\",\n        \"status\": \"ok\",\n        \"note\": \"DDG HTML SERP, 10 results\"\n      },\n      {\n        \"id\": \"Q2\",\n        \"tool\": \"webfetch\",\n        \"url\": \"https://duckduckgo.com/html/?q=qdrant+colbert+late+interaction+reranking\",\n        \"status\": \"ok\",\n        \"note\": \"DDG HTML SERP, 10 results\"\n      },\n      {\n        \"id\": \"Q3\",\n        \"tool\": \"webfetch\",\n        \"url\": \"https://duckduckgo.com/html/?q=qdrant+docker+local+deployment+memory+usage+resource+requirements+small+scale\",\n        \"status\": \"ok\",\n        \"note\": \"DDG HTML SERP, 10 results\"\n      },\n      {\n        \"id\": \"Q4\",\n        \"tool\": \"webfetch\",\n        \"url\": \"https://duckduckgo.com/html/?q=colbert+late+interaction+reranking+cost+latency+tradeoffs+benchmark\",\n        \"status\": \"ok\",\n        \"note\": \"DDG HTML SERP, 10 results\"\n      },\n      {\n        \"id\": \"Q5\",\n        \"tool\": \"webfetch\",\n        \"url\": \"https://duckduckgo.com/html/?q=sqlite-vec+vs+qdrant+embedded+vector+database+comparison\",\n        \"status\": \"failed\",\n        \"note\": \"DuckDuckGo bot CAPTCHA page returned; no results. Receipt preserved. Comparative embedded-vs-server query not executed; not retried.\"\n      }\n    ],\n    \"sources_discovered\": 25,\n    \"sources_selected\": 6,\n    \"sources_read\": 6\n  },\n  \"repo_grounding\": {\n    \"note\": \"Required source class 'repo' satisfied via direct code receipts from the harness repo (/mnt/workdrive/issue161-harness).\",\n    \"receipts\": [\n      {\n        \"id\": \"R1\",\n        \"path\": \"src/rune/memory_store.py\",\n        \"evidence\": \"line 5 'file running sqlite-vec (dense vectors) + FTS5 (BM25) side by side'; line 10 'HYBRID RETRIEVAL: dense (vec0) + BM25 (FTS5) fused by RRF'; lines 122-124 sqlite_vec.load(db); lines 129/149 entries_fts/chunks_fts fts5 virtual tables; lines 677-679 BM25-via-FTS5 recall path; line 856 conjunctive BM25 handling\",\n        \"method\": \"grep\"\n      },\n      {\n        \"id\": \"R2\",\n        \"path\": \"pyproject.toml\",\n        \"evidence\": \"memory extra = [\\\"sqlite-vec>=0.1.0\\\"]; no qdrant dependency anywhere in pyproject\",\n        \"method\": \"grep\"\n      },\n      {\n        \"id\": \"R3\",\n        \"path\": \"src/rune/**/*.py\",\n        \"evidence\": \"case-insensitive grep for 'qdrant' across src/rune returned ZERO matches — no Qdrant code exists; the spike is a projection/comparative study, not an existing integration\",\n        \"method\": \"grep\"\n      },\n      {\n        \"id\": \"R4\",\n        \"path\": \"task_tree.json INWARD context\",\n        \"evidence\": \"keyword claims I1-I5 (memory_store.py, sleep_time.py, canary_p1_07.py, curator.py, rune_tui.py) carried forward; umbrella 'memory' matches 7 modules incl. memory_selector, retrieval_benchmark\",\n        \"method\": \"read\"\n      }\n    ]\n  },\n  \"sources\": [\n    {\n      \"id\": \"O1\",\n      \"url\": \"https://qdrant.tech/documentation/search/hybrid-queries/\",\n      \"title\": \"Hybrid Queries - Qdrant (official docs)\",\n      \"source_class\": \"external\",\n      \"type\": \"vendor_documentation\",\n      \"authority\": \"official\",\n      \"classification\": \"APPLICABLE_DIRECT\",\n      \"selected\": true,\n      \"read\": true,\n      \"read_receipt\": \"webfetch 200; full page captured (output truncated to tool-output file tool_g001a087e977ad001HEG21pT0W; core sections read in-context)\",\n      \"discovered_via\": \"Q1\"\n    },\n    {\n      \"id\": \"O2\",\n      \"url\": \"https://qdrant.tech/documentation/search/text-search/hybrid-search/\",\n      \"title\": \"Hybrid Search - Qdrant (official docs)\",\n      \"source_class\": \"external\",\n      \"type\": \"vendor_documentation\",\n      \"authority\": \"official\",\n      \"classification\": \"APPLICABLE_DIRECT\",\n      \"selected\": false,\n      \"read\": false,\n      \"discovered_via\": \"Q1\",\n      \"note\": \"dense+sparse via prefetch API + RRF; redundant with O1 which was read in full\"\n    },\n    {\n      \"id\": \"O3\",\n      \"url\": \"https://github.com/qdrant/qdrant\",\n      \"title\": \"qdrant/qdrant Line truncated
+{"type":"step_finish","timestamp":1788986768086,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ebbab70014YdVXXsFM","reason":"tool-calls","snapshot":"2684feb5c5e463183f23c6aeb792e1dd2828de36","messageID":"msg_g001a087e99b91001xdHu0A7Eo","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":89097,"input":5442,"output":8839,"reasoning":0,"cache":{"write":0,"read":74816}},"cost":0}}
+{"type":"step_start","timestamp":1788986771535,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ebc84d001jx6LTQng5","messageID":"msg_g001a087ebbb24001VjTdPN0ME","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"245d4ca83367c1a6c35538ef7794fb9fe677a72f","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986772755,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"bash","callID":"call_67635801f09d4bdfaf54a5c3","state":{"status":"completed","input":{"command":"python3 -c \"import json; d=json.load(open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json')); print('valid JSON;', len(d['sources']), 'sources;', len(d['evidence']), 'evidence blocks;', len(d['discovery']['queries']), 'queries')\" && tail -1 /mnt/workdrive/issue161-harness/research/issue-162/outward.json","description":"Validate artifact JSON and completion marker"},"output":"Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\n    import json; d=json.load(open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json')); print('valid JSON;', len(d['sources']), 'sources;', len(d['evidence']), 'evidence blocks;', len(d['discovery']['queries']), 'queries')\n                   ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.14/json/__init__.py\", line 298, in load\n    return loads(fp.read(),\n        cls=cls, object_hook=object_hook,\n        parse_float=parse_float, parse_int=parse_int,\n        parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)\n  File \"/usr/lib/python3.14/json/__init__.py\", line 352, in loads\n    return _default_decoder.decode(s)\n           ~~~~~~~~~~~~~~~~~~~~~~~^^^\n  File \"/usr/lib/python3.14/json/decoder.py\", line 348, in decode\n    raise JSONDecodeError(\"Extra data\", s, end)\njson.decoder.JSONDecodeError: Extra data: line 499 column 1 (char 24483)\n","metadata":{"output":"Traceback (most recent call last):\n  File \"<string>\", line 1, in <module>\n    import json; d=json.load(open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json')); print('valid JSON;', len(d['sources']), 'sources;', len(d['evidence']), 'evidence blocks;', len(d['discovery']['queries']), 'queries')\n                   ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.14/json/__init__.py\", line 298, in load\n    return loads(fp.read(),\n        cls=cls, object_hook=object_hook,\n        parse_float=parse_float, parse_int=parse_int,\n        parse_constant=parse_constant, object_pairs_hook=object_pairs_hook, **kw)\n  File \"/usr/lib/python3.14/json/__init__.py\", line 352, in loads\n    return _default_decoder.decode(s)\n           ~~~~~~~~~~~~~~~~~~~~~~~^^^\n  File \"/usr/lib/python3.14/json/decoder.py\", line 348, in decode\n    raise JSONDecodeError(\"Extra data\", s, end)\njson.decoder.JSONDecodeError: Extra data: line 499 column 1 (char 24483)\n","exit":1,"description":"Validate artifact JSON and completion marker","truncated":false},"title":"Validate artifact JSON and completion marker","time":{"start":1788986772748,"end":1788986772753}},"id":"prt_g001a087ebc84e00190e3Vhndk","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","messageID":"msg_g001a087ebbb24001VjTdPN0ME"}}
+{"type":"step_finish","timestamp":1788986772803,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ebcd13001sNW7wO0zJ","reason":"tool-calls","snapshot":"096baa5655f1c95f744e9700e9b9960ecf2ab0a3","messageID":"msg_g001a087ebbb24001VjTdPN0ME","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":86914,"input":6549,"output":109,"reasoning":0,"cache":{"write":0,"read":80256}},"cost":0}}
+{"type":"step_start","timestamp":1788986778919,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ebe525001uoVZJgMTl","messageID":"msg_g001a087ebcd6e001JEx6oAbDO","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"3d7560014aadb9a4db9a870db5fa2b8917744686","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986781873,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"type":"tool","tool":"bash","callID":"call_4b4474c8961840c08fe15c74","state":{"status":"completed","input":{"command":"python3 - <<'EOF'\nimport json\nraw = open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json').read()\nmarker = 'StageCompleted: OUTWARD'\nbody, _, tail = raw.rpartition(marker)\nbody = body.rstrip().rstrip('\\n')\nd = json.loads(body)\njson.dump(d, open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json','w'), indent=2, ensure_ascii=False)\nopen('/mnt/workdrive/issue161-harness/research/issue-162/outward.json','a').write('\\n' + marker + '\\n')\nd2 = json.loads(open('/mnt/workdrive/issue161-harness/research/issue-162/outward.json').read().rpartition(marker)[0].rstrip())\nprint('valid;', len(d2['sources']), 'sources;', len(d2['evidence']), 'evidence blocks;', len(d2['discovery']['queries']), 'queries')\nEOF","description":"Re-serialize artifact as clean JSON + marker line"},"output":"valid; 25 sources; 7 evidence blocks; 5 queries\n","metadata":{"output":"valid; 25 sources; 7 evidence blocks; 5 queries\n","exit":0,"description":"Re-serialize artifact as clean JSON + marker line","truncated":false},"title":"Re-serialize artifact as clean JSON + marker line","time":{"start":1788986781867,"end":1788986781871}},"id":"prt_g001a087ebe527001XX38dBcS1","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","messageID":"msg_g001a087ebcd6e001JEx6oAbDO"}}
+{"type":"step_finish","timestamp":1788986781899,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ebf0b0001wfWgdlLWC","reason":"tool-calls","snapshot":"8f2830ff19469e6cc0ebb24a53ec4f8074e6d662","messageID":"msg_g001a087ebcd6e001JEx6oAbDO","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":87424,"input":344,"output":232,"reasoning":0,"cache":{"write":0,"read":86848}},"cost":0}}
+{"type":"step_start","timestamp":1788986789687,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ec0f35001cVVYG25wr","messageID":"msg_g001a087ebf0f5001whHxHyt90","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","snapshot":"8821e3121c9d35274d334d485c4480ff1249eae5","type":"step-start"}}
+{"type":"text","timestamp":1788986798925,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ec0f40002XJQhOxF2j","messageID":"msg_g001a087ebf0f5001whHxHyt90","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"text","text":"OUTWARD stage for issue #162 is complete. Artifact: `/mnt/workdrive/issue161-harness/research/issue-162/outward.json` (validated JSON + `StageCompleted: OUTWARD`).\n\n**What actually happened**\n\n**Discovery — 5 real DDG SERP queries, receipts preserved:**\n- Q1–Q4 OK (hybrid docs, ColBERT reranking, deployment/memory footprint, ColBERT trade-offs) → ~25 candidate URLs\n- Q5 (`sqlite-vec vs qdrant embedded comparison`) **failed** on a DuckDuckGo bot CAPTCHA — recorded as a limitation, not retried\n\n**Sources — O1–O25 classified** (vendor docs, official repo, primary papers, community, mirrors). **6 read** with receipts: O1 (Qdrant Hybrid Queries docs, full), O9 (Multivectors/late-interaction tutorial, full), O3 (qdrant/qdrant README via raw.githubusercontent + page), O12 (ColBERT arXiv abstract), O11 (Weaviate late-interaction overview), plus repo grounding R1–R4.\n\n**Repo class receipts (grep-verified):** `memory_store.py` = sqlite-vec dense + FTS5 BM25 fused by RRF (lines 5, 10, 122–124); `pyproject.toml` has only `sqlite-vec>=0.1.0`; **zero** Qdrant matches in `src/rune/` — the spike is a projection study, no existing integration.\n\n**Key evidence claims (E1–E7):**\n- Qdrant Query API: nested prefetch + RRF/DBSF fusion; raw-score alpha-weighting documented as unreliable due to dense/sparse scale mismatch — directly mirrors Rune's known memory_selector raw-score ranking bias\n- ColBERT multivector is native (`MultiVectorComparator.MAX_SIM`) but official docs warn default usage causes \"massive RAM overhead, slow inserts\"; safe pattern is `hnsw m=0` rescore-only\n- ColBERT (SIGIR 2020): 100x faster, 10,000x fewer FLOPs vs BERT rerankers; independent (Weaviate) analysis: multivector storage ~2–5x dense even with ColBERTv2 compression\n- **Qdrant Edge** (in-process, embedded) discovered in the README — the only Qdrant mode compatible with Rune's local-first posture, but its maturity and feature surface (sparse/multivector support?) are an open question; the full-featured server is client-server Docker\n\n**Contradictions recorded:** native feature vs non-default safe config; ColBERTv2 compression not mentioned for Qdrant-stored multivectors; Edge embedded story vs server's no-RAM-ceiling (maintainer-confirmed).\n\nPer the stage contract: no synthesis, no design, no code changes, and research stopped once the evidence requirement (≥2 URLs read + repo receipts) was satisfied.","time":{"start":1788986789696,"end":1788986798924}}}
+{"type":"step_finish","timestamp":1788986798945,"sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","part":{"id":"prt_g001a087ec334d001FB3Rlik2I","reason":"stop","snapshot":"0410afd7a0138872a228893ec0079f72688f3159","messageID":"msg_g001a087ebf0f5001whHxHyt90","sessionID":"ses_-ffe5f78183255ffeT8vvlzqHA","type":"step-finish","tokens":{"total":88076,"input":210,"output":634,"reasoning":0,"cache":{"write":0,"read":87232}},"cost":0}}
@@ -0,0 +1,237 @@
+{
+  "issue": 162,
+  "round": 1,
+  "current_stage": "OUTWARD",
+  "completed_stages": [
+    "ISSUE",
+    "INWARD"
+  ],
+  "artifacts": {
+    "ISSUE": {
+      "contract": {
+        "issue": 162,
+        "title": "Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)",
+        "question_type": "mixed",
+        "sub_questions": [
+          "Address: Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)"
+        ],
+        "required_stages": [
+          "ISSUE",
+          "INWARD",
+          "OUTWARD",
+          "ADVERSARIAL",
+          "INNOVATION",
+          "SYNTHESIS",
+          "QUALIFY"
+        ],
+        "skipped_stages": {
+          "APPLICABILITY": "No OUTWARD research to ground against Rune."
+        },
+        "evidence_classes": [
+          "repo",
+          "external"
+        ],
+        "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+        "expected_artifact": "synthesis.json",
+        "ambiguous": false,
+        "needs_mimo": false,
+        "source": "deterministic"
+      },
+      "deterministic": true
+    },
+    "INWARD": {
+      "context": {
+        "keywords": [
+          "qdrant",
+          "associative",
+          "memory",
+          "projection",
+          "spike",
+          "dense",
+          "sparse",
+          "multivector",
+          "colbert",
+          "late",
+          "interaction",
+          "reranking",
+          "plain",
+          "summary",
+          "architecture_frontier_handoff",
+          "highest",
+          "value",
+          "retrieval",
+          "experiment",
+          "qdrant"
+        ],
+        "umbrella_matches": [
+          {
+            "umbrella": "memory",
+            "module": "memory_store",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "memory_consolidation",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "memory_env",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "query_memory",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "graph_memory",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "memory_selector",
+            "keyword": "memory"
+          },
+          {
+            "umbrella": "memory",
+            "module": "retrieval_benchmark",
+            "keyword": "retrieval"
+          }
+        ],
+        "candidate_files": [
+          "src/rune/memory_store.py",
+          "src/rune/sleep_time.py",
+          "src/rune/canary_p1_07.py",
+          "src/rune/curator.py",
+          "src/rune/rune_tui.py",
+          "src/rune/warm_router.py",
+          "src/rune/abstraction.py",
+          "src/rune/canary_full_system.py",
+          "src/rune/canary_p1_01.py",
+          "src/rune/memory_consolidation.py",
+          "src/rune/rune_operator.py",
+          "src/rune/cache.py",
+          "src/rune/canary_p1_02.py",
+          "src/rune/canary_p1_06.py",
+          "src/rune/canary_tui_drift.py"
+        ],
+        "candidate_tests": [
+          "tests/test_p1_03_memory_selection.py",
+          "tests/test_p1_07_runtime_objects.py",
+          "tests/test_retrieval_benchmark.py",
+          "tests/test_p0_07_inference_trace.py",
+          "tests/test_p1_01_capability_authority.py",
+          "tests/test_synthesis_executor.py",
+          "tests/test_context_broker.py",
+          "tests/test_failure_auto_filer.py",
+          "tests/test_p1_02_capsule_authority.py",
+          "tests/test_p1_06_model_routing.py"
+        ],
+        "define_contract": {
+          "issue": 162,
+          "title": "Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)",
+          "question_type": "mixed",
+          "sub_questions": [
+            "Address: Qdrant associative-memory projection spike (dense/sparse/multivector + ColBERT late-interaction reranking)"
+          ],
+          "required_stages": [
+            "ISSUE",
+            "INWARD",
+            "OUTWARD",
+            "ADVERSARIAL",
+            "INNOVATION",
+            "SYNTHESIS",
+            "QUALIFY"
+          ],
+          "skipped_stages": {
+            "APPLICABILITY": "No OUTWARD research to ground against Rune."
+          },
+          "evidence_classes": [
+            "repo",
+            "external"
+          ],
+          "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+          "expected_artifact": "synthesis.json",
+          "ambiguous": false,
+          "needs_mimo": false,
+          "source": "deterministic"
+        },
+        "mimo_needed": false
+      },
+      "deterministic": true,
+      "claims": [
+        {
+          "id": "I1",
+          "claim": "Relevant file: src/rune/memory_store.py",
+          "evidence": [
+            "src/rune/memory_store.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I2",
+          "claim": "Relevant file: src/rune/sleep_time.py",
+          "evidence": [
+            "src/rune/sleep_time.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I3",
+          "claim": "Relevant file: src/rune/canary_p1_07.py",
+          "evidence": [
+            "src/rune/canary_p1_07.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I4",
+          "claim": "Relevant file: src/rune/curator.py",
+          "evidence": [
+            "src/rune/curator.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I5",
+          "claim": "Relevant file: src/rune/rune_tui.py",
+          "evidence": [
+            "src/rune/rune_tui.py"
+          ],
+          "status": "CURRENT"
+        }
+      ]
+    }
+  },
+  "blocking_unknowns": [],
+  "status": "ACTIVE",
+  "stage_history": [
+    {
+      "stage": "ISSUE",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "contract",
+        "deterministic"
+      ]
+    },
+    {
+      "stage": "INWARD",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "context",
+        "deterministic",
+        "claims"
+      ]
+    },
+    {
+      "stage": "OUTWARD",
+      "round": 1,
+      "failed": true,
+      "reason": "OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \u2014 search snippets alone do not count as evidence"
+    }
+  ]
+}
@@ -0,0 +1,3 @@
+{"attempt_id": "issue-162-ISSUE-1-a1", "event_id": "issue-162-ISSUE-1", "stage": "ISSUE", "issue": 162, "process_id": "research-162-r1", "started_at": "2026-09-09T20:41:27.955220+00:00", "finished_at": "2026-09-09T20:41:28.148457+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.1933, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-162-INWARD-1-a1", "event_id": "issue-162-INWARD-1", "stage": "INWARD", "issue": 162, "process_id": "research-162-r1", "started_at": "2026-09-09T20:41:28.149060+00:00", "finished_at": "2026-09-09T20:41:28.297378+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.1484, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-162-OUTWARD-1-a1", "event_id": "issue-162-OUTWARD-1", "stage": "OUTWARD", "issue": 162, "process_id": "research-162-r1", "started_at": "2026-09-09T20:41:49.531028+00:00", "finished_at": "2026-09-09T20:48:41.608706+00:00", "terminal_status": "GATE_FAILED", "wall_time_s": 412.0777, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
@@ -0,0 +1 @@
+consumed at 1788984934.791921
@@ -0,0 +1 @@
+consumed at 1788984909.948637
@@ -0,0 +1 @@
+consumed at 1788984961.9986615
@@ -0,0 +1 @@
+consumed at 1788985330.2829049
@@ -0,0 +1,151 @@
+{
+  "stage": "OUTWARD",
+  "issue": 310,
+  "round": 1,
+  "subquestion": "ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path — model_time/tool_time always 0",
+  "required_source_classes": ["repo"],
+  "queries": [
+    {
+      "kind": "QUERY",
+      "tool": "Grep",
+      "pattern": "model_time|tool_time",
+      "scope": "whole repo",
+      "hits": 51,
+      "receipt": "matches in research/issue-310/task_tree.json, telemetry/attempts.jsonl (3 attempt records), outward.json (prior attempt), scripts/stage_telemetry.py:13,140,141,155,156, src/rune/rune_operator.py:1574, src/rune/inference_trace.py:69, docs/inference-trace.md:35, plans/2026-09-05-p0-07-inference-trace.md:78,120,158, canary_p0_07.py, and 5 test files (test_p0_07_inference_trace.py, test_p1_01/02/03/06)"
+    },
+    {
+      "kind": "QUERY",
+      "tool": "Grep",
+      "pattern": "mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start",
+      "scope": "whole repo",
+      "hits": 16,
+      "receipt": "ALL matches confined to: scripts/stage_telemetry.py (docstring lines 24-25 + definitions 83-115), tests/test_stage_telemetry.py:62-63,77 (invocations), and research/issue-310 artifacts (prior report + events log). ZERO matches in src/ and ZERO in scripts/ outside stage_telemetry.py itself."
+    },
+    {
+      "kind": "QUERY",
+      "tool": "Grep",
+      "pattern": "StageAttempt|stage_telemetry",
+      "scope": "whole repo",
+      "hits": 47,
+      "receipt": "Production importers: scripts/research_stage_executor.py:87-91 ONLY. Tests: tests/test_stage_telemetry.py. src/: zero matches (src/rune has no StageAttempt reference)."
+    },
+    {
+      "kind": "QUERY",
+      "tool": "Grep",
+      "pattern": "ResearchEventRelay|elapsed",
+      "include": "scripts/research_stage_executor.py",
+      "hits": 20,
+      "receipt": "5 relay invocations (lines 363-364, 585-586, 755-756, 917-918, 1072-1073, 1182-1183), each followed by relay_result['elapsed'] extraction (lines 501, 658, 811, 964, 1243, 1306, 1407); line 1215 shows a no-op relay_result with elapsed 0.0. No StageAttempt/telemetry references anywhere in the executor's stage bodies."
+    },
+    {
+      "kind": "SOURCE_READ",
+      "tool": "Read",
+      "target": "scripts/stage_telemetry.py",
+      "lines": "1-221 (full)"
+    },
+    {
+      "kind": "SOURCE_READ",
+      "tool": "Read",
+      "target": "scripts/research_stage_executor.py",
+      "lines": "60-129"
+    },
+    {
+      "kind": "SOURCE_READ",
+      "tool": "Read",
+      "target": "tests/test_stage_telemetry.py",
+      "lines": "50-109"
+    }
+  ],
+  "sources": [
+    {
+      "id": "O1",
+      "path": "scripts/stage_telemetry.py",
+      "classification": "PRIMARY",
+      "locus": "lines 2-28 (module docstring, OBS-1 epic #284/#287), 45-79 (StageAttempt.__init__: window lists + counters), 83-115 (mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end), 119-128 (finish() force-closes unclosed windows), 132-143 (summary(): model_time_s/tool_time_s = summed window pairs, explicitly non-additive), 186-218 (TelemetryLedger append-only persist, never raises)"
+    },
+    {
+      "id": "O2",
+      "path": "scripts/research_stage_executor.py",
+      "classification": "PRIMARY",
+      "locus": "lines 85-101: sole production importer; constructs StageAttempt + TelemetryLedger per stage event, runs _execute_stage, then calls finish(status-mapping) + persist. NO mark_* call between construction (line 89) and finish (line 96)."
+    },
+    {
+      "id": "O3",
+      "path": "tests/test_stage_telemetry.py",
+      "classification": "TEST_ONLY",
+      "locus": "lines 59-71 (only invocation site of mark_model_start/end + mark_tool_start/end in the entire repo), 74-81 (unclosed-window interrupt path)"
+    },
+    {
+      "id": "O4",
+      "path": "research/issue-310/telemetry/attempts.jsonl",
+      "classification": "EMPIRICAL",
+      "locus": "lines 1-3: real persisted production attempt records. ISSUE stage: wall 0.1597s, model_time_s=0, tool_time_s=0, model_calls=0, tool_calls=0, window_counts all 0. INWARD stage: wall 0.2246s, same zeros. Prior OUTWARD attempt (GATE_FAILED, wall 315.06s): model_time_s=0, tool_time_s=0, model_calls=0, tool_calls=0 despite 315 seconds of real model+tool work — the strongest single datum for B1."
+    },
+    {
+      "id": "O5",
+      "path": "src/rune/inference_trace.py + src/rune/rune_operator.py",
+      "classification": "DISTINCT-SCHEMA",
+      "locus": "inference_trace.py:69 (InferenceTrace.model_time_ms field), rune_operator.py:1574 (model_time_ms=round(run_usage['duration_ns']/1e6, 3)) — a working, separately-persisted model-timing surface (Ollama total_duration via transport accumulators), NOT StageAttempt.model_time_s"
+    },
+    {
+      "id": "O6",
+      "path": "scripts/research_stage_executor.py (stage bodies)",
+      "classification": "ADJACENT",
+      "locus": "lines 363-364, 585-586, 755-756, 917-918, 1072-1073: every stage body runs the mimo worker subprocess via ResearchEventRelay and extracts only relay_result['elapsed'] (coarse wall-clock). ResearchEventRelay has no StageAttempt references — the executor/relay boundary is exactly where model/tool time accrues without being marked."
+    }
+  ],
+  "evidence": [
+    {
+      "id": "E1",
+      "source": "O1",
+      "claim": "StageAttempt defines four window-marker pairs (model, tool, gate, persistence) plus counters (model_calls, tool_calls, sources_discovered, ...); summary() derives model_time_s and tool_time_s by summing (end-start) monotonic window pairs; unclosed windows are force-closed at finish(); categories are explicitly non-additive vs wall_time.",
+      "locus": "scripts/stage_telemetry.py:59-79, 83-128, 132-143, 154-163"
+    },
+    {
+      "id": "E2",
+      "source": "O2",
+      "claim": "The stage executor is the ONLY production code importing stage_telemetry; it wraps every stage with StageAttempt(...)/finish(...)/ledger.persist(...) but NEVER calls any mark_* window marker or increments any counter between construction and finish — model_time_s/tool_time_s/window_counts are therefore structurally always 0 in production.",
+      "locus": "scripts/research_stage_executor.py:87-101"
+    },
+    {
+      "id": "E3",
+      "source": "O3",
+      "claim": "mark_model_start/mark_model_end/mark_tool_start/mark_tool_end are invoked only in tests/test_stage_telemetry.py:62-63,77; grep over the whole repo finds zero mark_* call sites in src/ and zero in scripts/ outside stage_telemetry.py's own definitions/docstring.",
+      "locus": "tests/test_stage_telemetry.py:62-63, 77"
+    },
+    {
+      "id": "E4",
+      "source": "O4",
+      "claim": "Empirical confirmation in this round's own production records: all three persisted attempts (ISSUE 0.1597s, INWARD 0.2246s, OUTWARD 315.06s wall) show model_time_s=0, tool_time_s=0, model_calls=0, tool_calls=0, window_counts all 0 — including the OUTWARD attempt that consumed 315 seconds of real model/tool work.",
+      "locus": "research/issue-310/telemetry/attempts.jsonl:1-3"
+    },
+    {
+      "id": "E5",
+      "source": "O6",
+      "claim": "The stage bodies' actual model invocation happens inside mimo worker subprocesses driven by ResearchEventRelay, which records only a coarse wall-clock 'elapsed'; relay results are folded into stage results but never into StageAttempt windows — the instrumentation gap is precisely at the executor/relay boundary.",
+      "locus": "scripts/research_stage_executor.py:363-364/501, 585-586/658, 755-756/811, 917-918/964, 1072-1073/1243"
+    },
+    {
+      "id": "E6",
+      "source": "O5",
+      "claim": "A similarly-named but separate timing surface exists and DOES function: InferenceTrace.model_time_ms is populated from Ollama transport usage_total_duration_ns in the operator path. This is NOT StageAttempt.model_time_s; conflation risk when reading ADAPT-1 claims about 'model_time'.",
+      "locus": "src/rune/inference_trace.py:69; src/rune/rune_operator.py:1574; docs/inference-trace.md:35"
+    },
+    {
+      "id": "E7",
+      "source": "O1",
+      "claim": "stage_telemetry.py self-documents the design constraint: observational only, every attempt persists its own record including failures, categories observed and non-additive. The executor's finish() status mapping (lines 96-100) covers COMPLETED/GATE_FAILED/FAILED/INTERRUPTED; TIMEOUT is defined in TERMINAL_STATUSES but not visible in the executor's mapping expression (out of B1 scope, noted as open).",
+      "locus": "scripts/stage_telemetry.py:2-28, 37; scripts/research_stage_executor.py:96-100"
+    }
+  ],
+  "limitations": [
+    "Grep receipts cover all file types repo-wide for the mark_* pattern (16 hits, no include filter), so the 'test-only invocation' finding is not limited to *.py.",
+    "Whether ResearchEventRelay itself or the mimo subprocess could emit window events that the executor drops was not traced into research_event_relay.py internals; however, grep for StageAttempt/mark_* shows the relay module never references telemetry, so no hidden call sites exist there.",
+    "TIMEOUT terminal-status handling: defined in stage_telemetry.py TERMINAL_STATUSES and force-closed at finish(), but the executor's status mapping expression does not map TIMEOUT; whether any caller can currently produce TIMEOUT was not traced (out of B1 scope).",
+    "The prior OUTWARD attempt's artifact (outward.json, GATE_FAILED) was overwritten by this refresh; prior attempt's query receipts are superseded by this run's, which were re-executed for real."
+  ],
+  "contradictions": [
+    "None found on B1 itself: static evidence (zero production call sites for mark_* markers, O2/O3) and empirical evidence (attempts.jsonl all zeros including a 315s attempt, O4) agree.",
+    "Near-contradiction resolved by disambiguation: InferenceTrace.model_time_ms (populated, O5) vs StageAttempt.model_time_s (always 0, O1/O2/O4) — same 'model_time' naming family, different pipelines; any source claiming 'model_time is populated' would be true of the former and false of the latter."
+  ]
+}
@@ -0,0 +1,29 @@
+{"type":"step_start","timestamp":1788985346754,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d60abf001bmTR46fhY","messageID":"msg_g001a087d5d05a001jO6g0Aq9i","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"718a4db6c63e87eeec5efeb65793abe4746e39be","type":"step-start"}}
+{"type":"text","timestamp":1788985348450,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d60cd3001DeIBXXXUf","messageID":"msg_g001a087d5d05a001jO6g0Aq9i","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"text","text":"I'll first check for a matching skill, then run the repo discovery for issue #310's telemetry-marker subquestion.","time":{"start":1788985347283,"end":1788985348446}}}
+{"type":"tool_use","timestamp":1788985348454,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"skill_search","callID":"call_3d6b1ffcb4f74ba18db8cd16","state":{"status":"completed","input":{"query":"Research stage outward: discover, classify, and read repo sources as evidence for a subquestion about telemetry markers never invoked in production path; preserve query/source receipts; no code modification. Input: local repository + issue #310 context. Output: evidence report with stable source IDs (O1, O2...) and receipts. Audience: research orchestrator."},"output":"{\n  \"status\": \"matched\",\n  \"results\": [\n    {\n      \"skill_id\": \"firecrawl-search\",\n      \"name\": \"firecrawl-search\",\n      \"score\": 0.5986,\n      \"reason\": \"The skill description matches these query terms: research, discover, source, about, in.\"\n    },\n    {\n      \"skill_id\": \"sales\",\n      \"name\": \"sales\",\n      \"score\": 0.58,\n      \"reason\": \"The skill description matches these query terms: research, evidence, invoked, context.\"\n    },\n    {\n      \"skill_id\": \"deep-research\",\n      \"name\": \"deep-research\",\n      \"score\": 0.5868,\n      \"reason\": \"The skill description matches these query terms: research, source, in, no, report.\"\n    }\n  ],\n  \"loaded_skill_id\": null\n}","metadata":{"status":"matched","loadedSkillID":null,"truncated":false},"title":"Found 3 skills","time":{"start":1788985348448,"end":1788985348451}},"id":"prt_g001a087d60cd9001UWTg9AbsF","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","messageID":"msg_g001a087d5d05a001jO6g0Aq9i"}}
+{"type":"step_finish","timestamp":1788985348556,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d61165001OAf5LV9A0","reason":"tool-calls","snapshot":"e7b2b0b9e2ece4c313227411877c11f10584f85a","messageID":"msg_g001a087d5d05a001jO6g0Aq9i","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":28884,"input":28476,"output":408,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788985362209,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d6471e0010pXeTPmXS","messageID":"msg_g001a087d61247001eDqV40rEk","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"c91e22924437b076977e941f13f15bcb4df51428","type":"step-start"}}
+{"type":"text","timestamp":1788985362742,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d647e7002HQC2UcHPk","messageID":"msg_g001a087d61247001eDqV40rEk","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"text","text":"No strong skill match (local-repo evidence task) — proceeding with direct repo discovery. First, locating the working repo and searching for the telemetry markers.","time":{"start":1788985362407,"end":1788985362739}}}
+{"type":"tool_use","timestamp":1788985362928,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"grep","callID":"call_8092e5f1bc0e42a2a9898330","state":{"status":"completed","input":{"pattern":"model_time|tool_time"},"output":"Found 51 matches\n/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json:\n  Line 13:         \"title\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\",\n\n  Line 16:           \"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\"\n\n  Line 53:           \"model_time\",\n\n  Line 54:           \"tool_time\",\n\n  Line 133:           \"title\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\",\n\n  Line 136:             \"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\"\n\n\n/mnt/workdrive/issue161-harness/research/issue-310/telemetry/attempts.jsonl:\n  Line 1: {\"attempt_id\": \"issue-310-ISSUE-1-a1\", \"event_id\": \"issue-310-ISSUE-1\", \"stage\": \"ISSUE\", \"issue\": 310, \"process_id\": \"research-310-r1\", \"started_at\": \"2026-09-09T20:15:09.949030+00:00\", \"finished_at\": \"2026-09-09T20:15:10.108621+00:00\", \"terminal_status\": \"COMPLETED\", \"wall_time_s\": 0.1597, \"model_time_s\": 0, \"tool_time_s\": 0, \"gate_time_s\": 0, \"persistence_time_s\": 0, \"overlap_note\": \"categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive\", \"model_calls\": 0, \"tool_calls\": 0, \"repo_read_calls\": 0, \"external_queries\": 0, \"sources_discovered\": 0, \"sources_read\": 0, \"retries\": 0, \"reconciliation_actions\": 0, \"implementation_corrections\": 0, \"ci_failures\": 0, \"input_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"output_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"queue_wait_s\": null, \"window_counts\": {\"model\": 0, \"tool\": 0, \"gate\": 0, \"persistence\": 0}}\n\n  Line 2: {\"attempt_id\": \"issue-310-INWARD-1-a1\", \"event_id\": \"issue-310-INWARD-1\", \"stage\": \"INWARD\", \"issue\": 310, \"process_id\": \"research-310-r1\", \"started_at\": \"2026-09-09T20:15:34.792311+00:00\", \"finished_at\": \"2026-09-09T20:15:35.016831+00:00\", \"terminal_status\": \"COMPLETED\", \"wall_time_s\": 0.2246, \"model_time_s\": 0, \"tool_time_s\": 0, \"gate_time_s\": 0, \"persistence_time_s\": 0, \"overlap_note\": \"categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive\", \"model_calls\": 0, \"tool_calls\": 0, \"repo_read_calls\": 0, \"external_queries\": 0, \"sources_discovered\": 0, \"sources_read\": 0, \"retries\": 0, \"reconciliation_actions\": 0, \"implementation_corrections\": 0, \"ci_failures\": 0, \"input_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"output_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"queue_wait_s\": null, \"window_counts\": {\"model\": 0, \"tool\": 0, \"gate\": 0, \"persistence\": 0}}\n\n  Line 3: {\"attempt_id\": \"issue-310-OUTWARD-1-a1\", \"event_id\": \"issue-310-OUTWARD-1\", \"stage\": \"OUTWARD\", \"issue\": 310, \"process_id\": \"research-310-r1\", \"started_at\": \"2026-09-09T20:16:01.999099+00:00\", \"finished_at\": \"2026-09-09T20:21:17.061293+00:00\", \"terminal_status\": \"GATE_FAILED\", \"wall_time_s\": 315.0622, \"model_time_s\": 0, \"tool_time_s\": 0, \"gate_time_s\": 0, \"persistence_time_s\": 0, \"overlap_note\": \"categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive\", \"model_calls\": 0, \"tool_calls\": 0, \"repo_read_calls\": 0, \"external_queries\": 0, \"sources_discovered\": 0, \"sources_read\": 0, \"retries\": 0, \"reconciliation_actions\": 0, \"implementation_corrections\": 0, \"ci_failures\": 0, \"input_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"output_tokens\": \"UNKNOWN_NOT_EXPOSED\", \"queue_wait_s\": null, \"window_counts\": {\"model\": 0, \"tool\": 0, \"gate\": 0, \"persistence\": 0}}\n\n\n/mnt/workdrive/issue161-harness/research/issue-310/outward.json:\n  Line 6:   \"subquestion\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path — model_time/tool_time always 0\",\n\n  Line 11:         \"query\": \"rg 'model_time|tool_time' src/\",\n\n  Line 43:         \"receipt\": \"both records show model_time_s=0, tool_time_s=0, gate_time_s=0, persistence_time_s=0, model_calls=0, tool_calls=0, window_counts all 0, wall_time_s 0.1597/0.2246\"\n\n  Line 58:         \"classification\": \"PRIMARY — the StageAttempt telemetry module (OBS-1, epic #284/#287); defines mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end, summary() deriving model_time_s/tool_time_s from summed windows\"\n\n  Line 86:         \"classification\": \"DISTINCT-SCHEMA — InferenceTrace.model_time_ms (line 69) is a different telemetry line (Ollama total_durationLine truncated
+{"type":"tool_use","timestamp":1788985363017,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"bash","callID":"call_2c28bd85b84d49e4931ff2d5","state":{"status":"completed","input":{"command":"pwd && ls","description":"Show current working directory contents"},"output":"/mnt/workdrive/issue161-harness\nAGENTS.md\nalternatives.json\nbackups\nconfig\ndocs\nhenxels_checks.py\nhenxels.yaml\nlint-baseline.json\nmemory\nplans\nPRD.md\nprompts\n__pycache__\npyproject.toml\npyright-baseline.json\npyrightconfig.json\nREADME.md\nreports\nrequirements-ci.txt\nresearch\nscripts\nshared\nspecs\nsrc\nsurvey\ntests\nwal-risks.json\n","metadata":{"output":"/mnt/workdrive/issue161-harness\nAGENTS.md\nalternatives.json\nbackups\nconfig\ndocs\nhenxels_checks.py\nhenxels.yaml\nlint-baseline.json\nmemory\nplans\nPRD.md\nprompts\n__pycache__\npyproject.toml\npyright-baseline.json\npyrightconfig.json\nREADME.md\nreports\nrequirements-ci.txt\nresearch\nscripts\nshared\nspecs\nsrc\nsurvey\ntests\nwal-risks.json\n","exit":0,"description":"Show current working directory contents","truncated":false},"title":"Show current working directory contents","time":{"start":1788985363014,"end":1788985363016}},"id":"prt_g001a087d647ed001GRmMBDVVA","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","messageID":"msg_g001a087d61247001eDqV40rEk"}}
+{"type":"step_finish","timestamp":1788985363254,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d64a490014oswwE8fD","reason":"tool-calls","snapshot":"21020e34a7f49f964f976f3842bda000aef31486","messageID":"msg_g001a087d61247001eDqV40rEk","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":28944,"input":28772,"output":172,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788985379644,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d68b3a0016Fc45pZx7","messageID":"msg_g001a087d64c75001IONestjtU","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"4c50677592c0f46e55158ad6d71787144d649bb2","type":"step-start"}}
+{"type":"text","timestamp":1788985380277,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d68c26001BJW6Lkjew","messageID":"msg_g001a087d64c75001IONestjtU","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"text","text":"The prior OUTWARD attempt for this stage failed its gate; I'll run the discovery fresh with real searches. Next: find all call sites of the `mark_*` telemetry markers and locate the StageAttempt usage in the production path.","time":{"start":1788985379878,"end":1788985380275}}}
+{"type":"tool_use","timestamp":1788985380293,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"grep","callID":"call_98aea15451f14ef79e790439","state":{"status":"completed","input":{"pattern":"StageAttempt|stage_telemetry"},"output":"Found 47 matches\n/mnt/workdrive/issue161-harness/research/issue-310/stage_OUTWARD.events.jsonl:\n  Line 7: {\"type\":\"tool_use\",\"timestamp\":1788985362928,\"sessionID\":\"ses_-ffe5f782a30b9ffeXheAHMyyt\",\"part\":{\"type\":\"tool\",\"tool\":\"grep\",\"callID\":\"call_8092e5f1bc0e42a2a9898330\",\"state\":{\"status\":\"completed\",\"input\":{\"pattern\":\"model_time|tool_time\"},\"output\":\"Found 51 matches\\n/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json:\\n  Line 13:         \\\"title\\\": \\\"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\",\\n\\n  Line 16:           \\\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\"\\n\\n  Line 53:           \\\"model_time\\\",\\n\\n  Line 54:           \\\"tool_time\\\",\\n\\n  Line 133:           \\\"title\\\": \\\"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\",\\n\\n  Line 136:             \\\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\"\\n\\n\\n/mnt/workdrive/issue161-harness/research/issue-310/telemetry/attempts.jsonl:\\n  Line 1: {\\\"attempt_id\\\": \\\"issue-310-ISSUE-1-a1\\\", \\\"event_id\\\": \\\"issue-310-ISSUE-1\\\", \\\"stage\\\": \\\"ISSUE\\\", \\\"issue\\\": 310, \\\"process_id\\\": \\\"research-310-r1\\\", \\\"started_at\\\": \\\"2026-09-09T20:15:09.949030+00:00\\\", \\\"finished_at\\\": \\\"2026-09-09T20:15:10.108621+00:00\\\", \\\"terminal_status\\\": \\\"COMPLETED\\\", \\\"wall_time_s\\\": 0.1597, \\\"model_time_s\\\": 0, \\\"tool_time_s\\\": 0, \\\"gate_time_s\\\": 0, \\\"persistence_time_s\\\": 0, \\\"overlap_note\\\": \\\"categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive\\\", \\\"model_calls\\\": 0, \\\"tool_calls\\\": 0, \\\"repo_read_calls\\\": 0, \\\"external_queries\\\": 0, \\\"sources_discovered\\\": 0, \\\"sources_read\\\": 0, \\\"retries\\\": 0, \\\"reconciliation_actions\\\": 0, \\\"implementation_corrections\\\": 0, \\\"ci_failures\\\": 0, \\\"input_tokens\\\": \\\"UNKNOWN_NOT_EXPOSED\\\", \\\"output_tokens\\\": \\\"UNKNOWN_NOT_EXPOSED\\\", \\\"queue_wait_s...\n  Line 11: {\"type\":\"text\",\"timestamp\":1788985380277,\"sessionID\":\"ses_-ffe5f782a30b9ffeXheAHMyyt\",\"part\":{\"id\":\"prt_g001a087d68c26001BJW6Lkjew\",\"messageID\":\"msg_g001a087d64c75001IONestjtU\",\"sessionID\":\"ses_-ffe5f782a30b9ffeXheAHMyyt\",\"type\":\"text\",\"text\":\"The prior OUTWARD attempt for this stage failed its gate; I'll run the discovery fresh with real searches. Next: find all call sites of the `mark_*` telemetry markers and locate the StageAttempt usage in the production path.\",\"time\":{\"start\":1788985379878,\"end\":1788985380275}}}\n\n\n/mnt/workdrive/issue161-harness/research/issue-310/outward.json:\n  Line 13:         \"receipt\": \"src/rune/rune_operator.py:1574; src/rune/inference_trace.py:69; src/rune/canary_p0_07.py:57,162,195,224 (7 files total incl. 4 tests); scripts/stage_telemetry.py:13,140,141,155,156\"\n\n  Line 17:         \"query\": \"rg 'StageAttempt|TelemetryLedger' (whole repo, *.py)\",\n\n  Line 19:         \"receipt\": \"27 matches: scripts/stage_telemetry.py (self), scripts/research_stage_executor.py:87-91 (sole production importer), tests/test_stage_telemetry.py (test only)\"\n\n  Line 25:         \"receipt\": \"10 matches, ALL inside scripts/stage_telemetry.py (definitions+docstring); zero call sites in scripts/; src/ has zero matches (separate grep Q1-adjacent)\"\n\n  Line 31:         \"receipt\": \"src/ telemetry: only src/rune/orchestration/capability.py:24 (string literal 'telemetry' in capability list); StageAttempt-category names: 0 matches in src/\"\n\n  Line 35:         \"query\": \"grep stage_telemetry importers across scripts/ src/ tests/ (bash grep)\",\n\n  Line 55:         \"path\": \"scripts/stage_telemetry.py\",\n\n  Line 58:         \"classification\": \"PRIMARY — the StageAttempt telemetry module (OBS-1, epic #284/#287); defines mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end, summary() deriving model_time_s/tool_time_s from summed windows\"\n\n  Line 65:         \"classification\": \"PRIMARY — sole production importer of stage_telemetry (lines 87-91); constructs StageAttempt + TelemetryLedger per stage event, calls only finish() + persist()\"\n\n  Line 69:         \"path\": \"tests/test_stage_telemetry.py\",\n\n  Line 79:         \"classification\": \"ADJACENT — runs the actual mimo worker subprocess for OUTWARD; carries its Line truncated
+{"type":"tool_use","timestamp":1788985380297,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"grep","callID":"call_9bd939f8b8fe431ca886675b","state":{"status":"completed","input":{"pattern":"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start"},"output":"Found 16 matches\n/mnt/workdrive/issue161-harness/research/issue-310/stage_OUTWARD.events.jsonl:\n  Line 7: {\"type\":\"tool_use\",\"timestamp\":1788985362928,\"sessionID\":\"ses_-ffe5f782a30b9ffeXheAHMyyt\",\"part\":{\"type\":\"tool\",\"tool\":\"grep\",\"callID\":\"call_8092e5f1bc0e42a2a9898330\",\"state\":{\"status\":\"completed\",\"input\":{\"pattern\":\"model_time|tool_time\"},\"output\":\"Found 51 matches\\n/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json:\\n  Line 13:         \\\"title\\\": \\\"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\",\\n\\n  Line 16:           \\\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\"\\n\\n  Line 53:           \\\"model_time\\\",\\n\\n  Line 54:           \\\"tool_time\\\",\\n\\n  Line 133:           \\\"title\\\": \\\"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\",\\n\\n  Line 136:             \\\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\\\u2014 model_time/tool_time always 0\\\"\\n\\n\\n/mnt/workdrive/issue161-harness/research/issue-310/telemetry/attempts.jsonl:\\n  Line 1: {\\\"attempt_id\\\": \\\"issue-310-ISSUE-1-a1\\\", \\\"event_id\\\": \\\"issue-310-ISSUE-1\\\", \\\"stage\\\": \\\"ISSUE\\\", \\\"issue\\\": 310, \\\"process_id\\\": \\\"research-310-r1\\\", \\\"started_at\\\": \\\"2026-09-09T20:15:09.949030+00:00\\\", \\\"finished_at\\\": \\\"2026-09-09T20:15:10.108621+00:00\\\", \\\"terminal_status\\\": \\\"COMPLETED\\\", \\\"wall_time_s\\\": 0.1597, \\\"model_time_s\\\": 0, \\\"tool_time_s\\\": 0, \\\"gate_time_s\\\": 0, \\\"persistence_time_s\\\": 0, \\\"overlap_note\\\": \\\"categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive\\\", \\\"model_calls\\\": 0, \\\"tool_calls\\\": 0, \\\"repo_read_calls\\\": 0, \\\"external_queries\\\": 0, \\\"sources_discovered\\\": 0, \\\"sources_read\\\": 0, \\\"retries\\\": 0, \\\"reconciliation_actions\\\": 0, \\\"implementation_corrections\\\": 0, \\\"ci_failures\\\": 0, \\\"input_tokens\\\": \\\"UNKNOWN_NOT_EXPOSED\\\", \\\"output_tokens\\\": \\\"UNKNOWN_NOT_EXPOSED\\\", \\\"queue_wait_s...\n\n/mnt/workdrive/issue161-harness/research/issue-310/outward.json:\n  Line 58:         \"classification\": \"PRIMARY — the StageAttempt telemetry module (OBS-1, epic #284/#287); defines mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end, summary() deriving model_time_s/tool_time_s from summed windows\"\n\n  Line 72:         \"classification\": \"TEST_ONLY — the ONLY place mark_model_start/mark_tool_start are ever invoked (e.g. lines 62-63, 77); confirms markers are exercised exclusively in tests\"\n\n  Line 131:         \"claim\": \"mark_model_start/mark_model_end/mark_tool_start/mark_tool_end are invoked only in tests/test_stage_telemetry.py; no call sites exist anywhere in scripts/ outside stage_telemetry.py itself and none in src/.\",\n\n  Line 187:     {\"kind\": \"QUERY\", \"tool\": \"Grep\", \"pattern\": \"stage_telemetry|StageAttempt|mark_model_start|mark_tool_start|TelemetryLedger\", \"scope\": \"repo *.py\", \"hits\": 27},\n\n\n/mnt/workdrive/issue161-harness/tests/test_stage_telemetry.py:\n  Line 62:     a.mark_model_start(); a.mark_model_end()\n\n  Line 63:     a.mark_tool_start(); a.mark_tool_end()\n\n  Line 77:     a.mark_model_start()\n\n\n/mnt/workdrive/issue161-harness/scripts/stage_telemetry.py:\n  Line 24:   handle.mark_model_start/end()       → model invocation windows\n\n  Line 25:   handle.mark_tool_start/end()        → tool execution windows\n\n  Line 83:     def mark_model_start(self) -> None:\n\n  Line 86:     def mark_model_end(self) -> None:\n\n  Line 92:     def mark_tool_start(self) -> None:\n\n  Line 95:     def mark_tool_end(self) -> None:\n\n  Line 101:     def mark_gate_start(self) -> None:\n\n  Line 109:     def mark_persistence_start(self) -> None:\n","metadata":{"matches":16,"truncated":false},"title":"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start","time":{"start":1788985380276,"end":1788985380295}},"id":"prt_g001a087d68c2d001Ff5cnQj8i","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","messageID":"msg_g001a087d64c75001IONestjtU"}}
+{"type":"step_finish","timestamp":1788985380320,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d68dc8001biGt36Z5R","reason":"tool-calls","snapshot":"2fccfea23d5910b09c340704630276479a3b4090","messageID":"msg_g001a087d64c75001IONestjtU","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":32057,"input":31846,"output":211,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788985395039,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d6c75b001w3KzgVEy3","messageID":"msg_g001a087d68e0800100ieT3dki","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"e147cbbc339d3c2941e3d7acbc4c2c60eaaa39d3","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985395891,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"read","callID":"call_d210b4d227f64e839a621fa6","state":{"status":"completed","input":{"file_path":"/mnt/workdrive/issue161-harness/tests/test_stage_telemetry.py","limit":60,"offset":50},"output":"<path>/mnt/workdrive/issue161-harness/tests/test_stage_telemetry.py</path>\n<type>file</type>\n<content>\n50: \n51: def _executor(tree):\n52:     return rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=tree.round)\n53: \n54: \n55: def _ledger(tree):\n56:     return st.TelemetryLedger(tree.artifact_dir)\n57: \n58: \n59: def test_unit_attempt_lifecycle(tmp_path):\n60:     \"\"\"Unit: begin → windows → finish produces a complete record.\"\"\"\n61:     a = st.StageAttempt(\"A1\", \"E1\", \"OUTWARD\", 1, \"research-1-r1\")\n62:     a.mark_model_start(); a.mark_model_end()\n63:     a.mark_tool_start(); a.mark_tool_end()\n64:     a.finish(\"COMPLETED\")\n65:     s = a.summary()\n66:     assert s[\"terminal_status\"] == \"COMPLETED\"\n67:     assert s[\"model_calls\"] == 1 and s[\"tool_calls\"] == 1\n68:     assert s[\"input_tokens\"] == \"UNKNOWN_NOT_EXPOSED\"\n69:     assert s[\"wall_time_s\"] is not None\n70:     # Non-additive note present\n71:     assert \"not additive\" in s[\"overlap_note\"]\n72: \n73: \n74: def test_unclosed_windows_closed_on_interrupt(tmp_path):\n75:     \"\"\"INTERRUPTED path: unclosed windows are closed at finish(), not lost.\"\"\"\n76:     a = st.StageAttempt(\"A2\", \"E2\", \"OUTWARD\", 1, \"p\")\n77:     a.mark_model_start()\n78:     a.finish(\"INTERRUPTED\")\n79:     assert a.summary()[\"window_counts\"][\"model\"] == 1\n80:     s, e = a.model_windows[0]\n81:     assert e > s\n82: \n83: \n84: def test_invalid_terminal_status_rejected():\n85:     a = st.StageAttempt(\"A3\", \"E3\", \"X\", 1, \"p\")\n86:     with pytest.raises(AssertionError):\n87:         a.finish(\"MAYBE\")\n88: \n89: \n90: def test_ledger_persists_and_reloads(tmp_path):\n91:     tree = _make_tree(tmp_path)\n92:     led = _ledger(tree)\n93:     a1 = st.StageAttempt(\"A1\", \"E1\", \"OUTWARD\", tree.issue, \"p\")\n94:     a1.finish(\"COMPLETED\")\n95:     a2 = st.StageAttempt(\"A2\", \"E2\", \"OUTWARD\", tree.issue, \"p\")\n96:     a2.finish(\"GATE_FAILED\")\n97:     assert led.persist(a1) and led.persist(a2)\n98:     # Reload survives \"restart\" (new ledger instance)\n99:     led2 = st.TelemetryLedger(tree.artifact_dir)\n100:     recs = led2.load_all()\n101:     assert len(recs) == 2\n102:     assert {r[\"terminal_status\"] for r in recs} == {\"COMPLETED\", \"GATE_FAILED\"}\n103: \n104: \n105: def test_ledger_persist_never_raises(tmp_path, monkeypatch):\n106:     \"\"\"Observational invariant: a broken telemetry sink must never break the stage.\"\"\"\n107:     tree = _make_tree(tmp_path)\n108:     led = _ledger(tree)\n109:     a = st.StageAttempt(\"A1\", \"E1\", \"OUTWARD\", tree.issue, \"p\")\n\n(Showing lines 50-109 of 194. Use offset=110 to continue.)\n</content>","metadata":{"preview":"\ndef _executor(tree):\n    return rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=tree.round)\n\n\ndef _ledger(tree):\n    return st.TelemetryLedger(tree.artifact_dir)\n\n\ndef test_unit_attempt_lifecycle(tmp_path):\n    \"\"\"Unit: begin → windows → finish produces a complete record.\"\"\"\n    a = st.StageAttempt(\"A1\", \"E1\", \"OUTWARD\", 1, \"research-1-r1\")\n    a.mark_model_start(); a.mark_model_end()\n    a.mark_tool_start(); a.mark_tool_end()\n    a.finish(\"COMPLETED\")\n    s = a.summary()\n    assert s[\"terminal_status\"] == \"COMPLETED\"\n    assert s[\"model_calls\"] == 1 and s[\"tool_calls\"] == 1\n    assert s[\"input_tokens\"] == \"UNKNOWN_NOT_EXPOSED\"\n    assert s[\"wall_time_s\"] is not None","truncated":true,"loaded":[]},"title":"tests/test_stage_telemetry.py","time":{"start":1788985395882,"end":1788985395890}},"id":"prt_g001a087d6c896001X7cfbqjWO","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","messageID":"msg_g001a087d68e0800100ieT3dki"}}
+{"type":"tool_use","timestamp":1788985395900,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"read","callID":"call_79f6a0ce6b0c43cb8fb28438","state":{"status":"completed","input":{"file_path":"/mnt/workdrive/issue161-harness/scripts/research_stage_executor.py","limit":70,"offset":60},"output":"<path>/mnt/workdrive/issue161-harness/scripts/research_stage_executor.py</path>\n<type>file</type>\n<content>\n60:     def execute(self, event: dict) -> dict:\n61:         \"\"\"Execute exactly one stage based on the ResearchStageReady event.\"\"\"\n62:         stage = event[\"stage\"]\n63:         attempt = event.get(\"attempt\", 1)\n64:         event_id = event.get(\"event_id\", make_event_id(\n65:             self.issue, f\"research-{self.issue}\", self.round_no, stage, attempt))\n66: \n67:         # Idempotency check: has this event already been consumed?\n68:         consumed_path = Path(self.artifact_dir) / f\".consumed_{event_id}\"\n69:         if consumed_path.exists():\n70:             return {\n71:                 \"status\": \"DUPLICATE\",\n72:                 \"event_id\": event_id,\n73:                 \"message\": f\"Event {event_id} already consumed — no-op\",\n74:             }\n75: \n76:         # Mark as consumed (idempotency)\n77:         consumed_path.parent.mkdir(parents=True, exist_ok=True)\n78:         consumed_path.write_text(f\"consumed at {time.time()}\")\n79: \n80:         self.event_log.append({\n81:             \"event_id\": event_id, \"stage\": stage, \"attempt\": attempt,\n82:             \"timestamp\": time.time(), \"action\": \"ACK\",\n83:         })\n84: \n85:         # OBS-1 telemetry: observational — every attempt records its own\n86:         # lifecycle (successes AND failures); never changes control flow.\n87:         from stage_telemetry import StageAttempt, TelemetryLedger\n88:         attempt_id = f\"{event_id}-a{attempt}\"\n89:         _attempt = StageAttempt(attempt_id, event_id, stage,\n90:                                 self.issue, f\"research-{self.issue}-r{self.round_no}\")\n91:         _ledger = TelemetryLedger(self.artifact_dir)\n92: \n93:         # Execute ONLY this stage\n94:         result = self._execute_stage(stage, attempt, event)\n95: \n96:         _attempt.finish(\n97:             \"COMPLETED\" if result.get(\"status\") == \"STAGE_COMPLETED\"\n98:             else (\"GATE_FAILED\" if result.get(\"status\") in (\"GATE_FAILED\", \"GATE_RETRY\")\n99:                   else (\"FAILED\" if result.get(\"status\", \"\").endswith(\"FAILED\")\n100:                         else result.get(\"status\", \"INTERRUPTED\"))))\n101:         _ledger.persist(_attempt)\n102: \n103:         # Runner-placement gate (RP2/#265): capture WHERE this actually ran\n104:         # and reject Pi-executed desktop-heavy stages as valid acceptance.\n105:         from runner_evidence import capture_execution_evidence, validate_placement, summarize_for_artifact\n106:         evidence = capture_execution_evidence(\n107:             stage=stage, issue=self.issue,\n108:             process_id=f\"research-{self.issue}-r{self.round_no}\",\n109:         )\n110:         placement_ok, placement_violations = validate_placement(evidence)\n111:         result[\"runner_evidence\"] = summarize_for_artifact(evidence)\n112:         if not placement_ok:\n113:             result[\"status\"] = \"PLACEMENT_REJECTED\"\n114:             result[\"placement_violations\"] = placement_violations\n115:             self.tree.fail(\"; \".join(placement_violations))\n116: \n117:         # Record the result\n118:         self.event_log.append({\n119:             \"event_id\": event_id, \"stage\": stage, \"attempt\": attempt,\n120:             \"timestamp\": time.time(),\n121:             \"action\": result[\"status\"],\n122:             \"artifact_hash\": result.get(\"artifact_hash\", \"\"),\n123:         })\n124: \n125:         # Persist the tree\n126:         self.tree.save()\n127: \n128:         return result\n129: \n\n(Showing lines 60-129 of 1532. Use offset=130 to continue.)\n</content>","metadata":{"preview":"    def execute(self, event: dict) -> dict:\n        \"\"\"Execute exactly one stage based on the ResearchStageReady event.\"\"\"\n        stage = event[\"stage\"]\n        attempt = event.get(\"attempt\", 1)\n        event_id = event.get(\"event_id\", make_event_id(\n            self.issue, f\"research-{self.issue}\", self.round_no, stage, attempt))\n\n        # Idempotency check: has this event already been consumed?\n        consumed_path = Path(self.artifact_dir) / f\".consumed_{event_id}\"\n        if consumed_path.exists():\n            return {\n                \"status\": \"DUPLICATE\",\n                \"event_id\": event_id,\n                \"message\": f\"Event {event_id} already consumed — no-op\",\n            }\n\n        # Mark as consumed (idempotency)\n        consumed_path.parent.mkdir(parents=True, exist_ok=True)\n        consumed_path.write_text(f\"consumed atLine truncated
+{"type":"step_finish","timestamp":1788985395920,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d6cabc001wYsUjyeYZ","reason":"tool-calls","snapshot":"e2de1549558c0813784dca0a88488aa5ab796be4","messageID":"msg_g001a087d68e0800100ieT3dki","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":35931,"input":35856,"output":75,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788985408614,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d6fc64001p0bKKeOQ2","messageID":"msg_g001a087d6caef001cSg8q8GcD","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"1d475c53d62e034c29684f75a7554b3f665de1f5","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985409730,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"grep","callID":"call_b0ad87c734ae4570bc3042aa","state":{"status":"completed","input":{"include":"scripts/research_stage_executor.py","pattern":"ResearchEventRelay|elapsed"},"output":"Found 20 matches\n/mnt/workdrive/issue161-harness/scripts/research_stage_executor.py:\n  Line 363:         from research_event_relay import ResearchEventRelay\n\n  Line 364:         relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 501:             \"elapsed\": relay_result[\"elapsed\"],\n\n  Line 585:         from research_event_relay import ResearchEventRelay\n\n  Line 586:         relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 658:             \"elapsed\": relay_result.get(\"elapsed\", 0.0),\n\n  Line 755:         from research_event_relay import ResearchEventRelay\n\n  Line 756:         relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 811:             \"elapsed\": relay_result.get(\"elapsed\", 0.0),\n\n  Line 917:         from research_event_relay import ResearchEventRelay\n\n  Line 918:         relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 964:             \"elapsed\": relay_result.get(\"elapsed\", 0.0),\n\n  Line 1072:         from research_event_relay import ResearchEventRelay\n\n  Line 1073:         relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 1182:             from research_event_relay import ResearchEventRelay\n\n  Line 1183:             relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)\n\n  Line 1215:             relay_result = {\"returncode\": 0, \"texts\": [], \"event_counts\": {}, \"receipts\": [], \"elapsed\": 0.0}\n\n  Line 1243:             \"elapsed\": relay_result.get(\"elapsed\", 0.0),\n\n  Line 1306:             \"elapsed\": relay_result.get(\"elapsed\", 0.0),\n\n  Line 1407:             \"elapsed\": relay_result[\"elapsed\"],\n","metadata":{"matches":20,"truncated":false},"title":"ResearchEventRelay|elapsed","time":{"start":1788985409720,"end":1788985409729}},"id":"prt_g001a087d6fe450011j6936Fva","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","messageID":"msg_g001a087d6caef001cSg8q8GcD"}}
+{"type":"tool_use","timestamp":1788985409735,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"read","callID":"call_10c53cfd725c42ff83c83db3","state":{"status":"completed","input":{"file_path":"/mnt/workdrive/issue161-harness/scripts/stage_telemetry.py"},"output":"<path>/mnt/workdrive/issue161-harness/scripts/stage_telemetry.py</path>\n<type>file</type>\n<content>\n1: #!/usr/bin/env python3\n2: \"\"\"stage_telemetry.py — StageAttempt telemetry (OBS-1, epic #284 / #287).\n3: \n4: OBSERVATIONAL ONLY. This module records what happened; it must never change\n5: stage authorization, retry behavior, model prompts, runner selection, or gate\n6: outcomes. Timing code is not a process authority.\n7: \n8: Design decisions (ratified in #287 tightening):\n9: - EVERY attempt persists its own lifecycle record — successful, gate-failed,\n10:   failed, timed-out, interrupted. Dropping expensive failures would bias\n11:   ADAPT-1's baseline toward cheap success.\n12: - Timing categories are OBSERVED, not forced additive: wall_time is not\n13:   model_time + tool_time when MiMo waits on a tool or relay overhead overlaps.\n14:   Records carry the raw timestamps so reports can distinguish exclusive /\n15:   overlapping / unmeasured-residual.\n16: - Records survive restart: each attempt is appended to\n17:   <artifact_dir>/telemetry/attempts.jsonl (append-only, one JSON object per\n18:   line) AND mirrored into the task-tree state at persist time.\n19: - UNKNOWN_NOT_EXPOSED is recorded verbatim when a counter (e.g. provider\n20:   tokens) is unavailable. Estimates are never presented as measurements.\n21: \n22: Attempt lifecycle (from the executor's perspective):\n23:   begin(attempt_id, event_id, stage)  → returns a handle\n24:   handle.mark_model_start/end()       → model invocation windows\n25:   handle.mark_tool_start/end()        → tool execution windows\n26:   handle.finish(terminal_status)      → COMPLETED | GATE_FAILED | FAILED |\n27:                                         TIMEOUT | INTERRUPTED\n28:   persist(handle)                     → append + mirror\n29: \"\"\"\n30: from __future__ import annotations\n31: \n32: import json\n33: import os\n34: import time\n35: from datetime import datetime, timezone\n36: \n37: TERMINAL_STATUSES = {\"COMPLETED\", \"GATE_FAILED\", \"FAILED\", \"TIMEOUT\", \"INTERRUPTED\"}\n38: UNKNOWN = \"UNKNOWN_NOT_EXPOSED\"\n39: \n40: \n41: def _now_iso() -> str:\n42:     return datetime.now(timezone.utc).isoformat()\n43: \n44: \n45: class StageAttempt:\n46:     \"\"\"One attempt's observed lifecycle. Pure data — no control flow.\"\"\"\n47: \n48:     def __init__(self, attempt_id: str, event_id: str, stage: str,\n49:                  issue: int, process_id: str):\n50:         self.attempt_id = attempt_id\n51:         self.event_id = event_id\n52:         self.stage = stage\n53:         self.issue = issue\n54:         self.process_id = process_id\n55:         self.started_at = _now_iso()\n56:         self._t0 = time.monotonic()\n57:         self.finished_at: str | None = None\n58:         self.terminal_status: str | None = None\n59:         # Observed windows (monotonic pairs, converted at finish)\n60:         self.model_windows: list[tuple[float, float]] = []\n61:         self.tool_windows: list[tuple[float, float]] = []\n62:         self.gate_windows: list[tuple[float, float]] = []\n63:         self.persistence_windows: list[tuple[float, float]] = []\n64:         # Counters\n65:         self.model_calls = 0\n66:         self.tool_calls = 0\n67:         self.repo_read_calls = 0\n68:         self.external_queries = 0\n69:         self.sources_discovered = 0\n70:         self.sources_read = 0\n71:         self.retries = 0\n72:         self.reconciliation_actions = 0\n73:         self.implementation_corrections = 0\n74:         self.ci_failures = 0\n75:         # Provider counters — recorded as UNKNOWN unless actually exposed\n76:         self.input_tokens: int | str = UNKNOWN\n77:         self.output_tokens: int | str = UNKNOWN\n78:         # Queue wait: measured by the caller if it knows the dispatch time\n79:         self.queue_wait_s: float | None = None\n80: \n81:     # -- window markers (observational; no control flow) ---------------------\n82: \n83:     def mark_model_start(self) -> None:\n84:         self.model_windows.append((time.monotonic(), 0.0))\n85: \n86:     def mark_model_end(self) -> None:\n87:         if self.model_windows and self.model_windows[-1][1] == 0.0:\n88:             s, _ = self.model_windows[-1]\n89:             self.model_windows[-1] = (s, time.monotonic())\n90:             self.model_calls += 1\n91: \n92:     def mark_tool_start(self) -> None:\n93:         self.tool_windows.append((time.monotonic(), 0.0))\n94: \n95:     def mark_tool_end(self) -> None:\n96:         if self.tool_windows and self.tool_windows[-1][1] == 0.0:\n97:             s, _ = self.tool_windows[-1]\n98:             self.tool_windows[-1] = (s, time.monotonicLine truncated
+{"type":"step_finish","timestamp":1788985409758,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d700c60019euAxnEWs","reason":"tool-calls","snapshot":"26531853c096af2dfe82309ceb73a4b02d46e5cb","messageID":"msg_g001a087d6caef001cSg8q8GcD","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":37657,"input":1701,"output":52,"reasoning":0,"cache":{"write":0,"read":35904}},"cost":0}}
+{"type":"step_start","timestamp":1788985439040,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d7733e001Gzox42Vwa","messageID":"msg_g001a087d70101001IbzxfkcSg","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"ca9736c07a0e9e0c01d49873bc31dbeacffef858","type":"step-start"}}
+{"type":"text","timestamp":1788985477733,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d77927001IvKW2wLOb","messageID":"msg_g001a087d70101001IbzxfkcSg","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"text","text":"All evidence is in hand. I'll now write the OUTWARD report to `research/issue-310/outward.json` (the prior gate-failed attempt's artifact in this same session, refreshed with this run's receipts).","time":{"start":1788985440551,"end":1788985477729}}}
+{"type":"tool_use","timestamp":1788985477746,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"type":"tool","tool":"write","callID":"call_593b9072c20046c79bb4da25","state":{"status":"completed","input":{"content":"{\n  \"stage\": \"OUTWARD\",\n  \"issue\": 310,\n  \"round\": 1,\n  \"subquestion\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path — model_time/tool_time always 0\",\n  \"required_source_classes\": [\"repo\"],\n  \"queries\": [\n    {\n      \"kind\": \"QUERY\",\n      \"tool\": \"Grep\",\n      \"pattern\": \"model_time|tool_time\",\n      \"scope\": \"whole repo\",\n      \"hits\": 51,\n      \"receipt\": \"matches in research/issue-310/task_tree.json, telemetry/attempts.jsonl (3 attempt records), outward.json (prior attempt), scripts/stage_telemetry.py:13,140,141,155,156, src/rune/rune_operator.py:1574, src/rune/inference_trace.py:69, docs/inference-trace.md:35, plans/2026-09-05-p0-07-inference-trace.md:78,120,158, canary_p0_07.py, and 5 test files (test_p0_07_inference_trace.py, test_p1_01/02/03/06)\"\n    },\n    {\n      \"kind\": \"QUERY\",\n      \"tool\": \"Grep\",\n      \"pattern\": \"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start\",\n      \"scope\": \"whole repo\",\n      \"hits\": 16,\n      \"receipt\": \"ALL matches confined to: scripts/stage_telemetry.py (docstring lines 24-25 + definitions 83-115), tests/test_stage_telemetry.py:62-63,77 (invocations), and research/issue-310 artifacts (prior report + events log). ZERO matches in src/ and ZERO in scripts/ outside stage_telemetry.py itself.\"\n    },\n    {\n      \"kind\": \"QUERY\",\n      \"tool\": \"Grep\",\n      \"pattern\": \"StageAttempt|stage_telemetry\",\n      \"scope\": \"whole repo\",\n      \"hits\": 47,\n      \"receipt\": \"Production importers: scripts/research_stage_executor.py:87-91 ONLY. Tests: tests/test_stage_telemetry.py. src/: zero matches (src/rune has no StageAttempt reference).\"\n    },\n    {\n      \"kind\": \"QUERY\",\n      \"tool\": \"Grep\",\n      \"pattern\": \"ResearchEventRelay|elapsed\",\n      \"include\": \"scripts/research_stage_executor.py\",\n      \"hits\": 20,\n      \"receipt\": \"5 relay invocations (lines 363-364, 585-586, 755-756, 917-918, 1072-1073, 1182-1183), each followed by relay_result['elapsed'] extraction (lines 501, 658, 811, 964, 1243, 1306, 1407); line 1215 shows a no-op relay_result with elapsed 0.0. No StageAttempt/telemetry references anywhere in the executor's stage bodies.\"\n    },\n    {\n      \"kind\": \"SOURCE_READ\",\n      \"tool\": \"Read\",\n      \"target\": \"scripts/stage_telemetry.py\",\n      \"lines\": \"1-221 (full)\"\n    },\n    {\n      \"kind\": \"SOURCE_READ\",\n      \"tool\": \"Read\",\n      \"target\": \"scripts/research_stage_executor.py\",\n      \"lines\": \"60-129\"\n    },\n    {\n      \"kind\": \"SOURCE_READ\",\n      \"tool\": \"Read\",\n      \"target\": \"tests/test_stage_telemetry.py\",\n      \"lines\": \"50-109\"\n    }\n  ],\n  \"sources\": [\n    {\n      \"id\": \"O1\",\n      \"path\": \"scripts/stage_telemetry.py\",\n      \"classification\": \"PRIMARY\",\n      \"locus\": \"lines 2-28 (module docstring, OBS-1 epic #284/#287), 45-79 (StageAttempt.__init__: window lists + counters), 83-115 (mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end), 119-128 (finish() force-closes unclosed windows), 132-143 (summary(): model_time_s/tool_time_s = summed window pairs, explicitly non-additive), 186-218 (TelemetryLedger append-only persist, never raises)\"\n    },\n    {\n      \"id\": \"O2\",\n      \"path\": \"scripts/research_stage_executor.py\",\n      \"classification\": \"PRIMARY\",\n      \"locus\": \"lines 85-101: sole production importer; constructs StageAttempt + TelemetryLedger per stage event, runs _execute_stage, then calls finish(status-mapping) + persist. NO mark_* call between construction (line 89) and finish (line 96).\"\n    },\n    {\n      \"id\": \"O3\",\n      \"path\": \"tests/test_stage_telemetry.py\",\n      \"classification\": \"TEST_ONLY\",\n      \"locus\": \"lines 59-71 (only invocation site of mark_model_start/end + mark_tool_start/end in the entire repo), 74-81 (unclosed-window interrupt path)\"\n    },\n    {\n      \"id\": \"O4\",\n      \"path\": \"research/issue-310/telemetry/attempts.jsonl\",\n      \"classification\": \"EMPIRICAL\",\n      \"locus\": \"lines 1-3: real persisted production attempt records. ISSUE stage: wall 0.1597s, model_time_s=0, tool_time_s=0, model_calls=0, tool_calls=0, window_counts all 0. INWARD stage: wall 0.2246s, same zeros. Prior OUTWARD attempt (GATE_FAILED, wall 315.06s): model_time_s=0, tool_time_s=0, model_calls=0, tool_calls=0 despite 315 seconds of real model+tool work — the strongest single datum for B1.\"\n    },\n    {\n      \"id\": \"O5\",\n      \"path\": \"src/rune/inference_trace.py + src/rune/rune_operator.py\",\n      \"classiLine truncated
+{"type":"step_finish","timestamp":1788985477771,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d80a720013msdVG7g3","reason":"tool-calls","snapshot":"326fd198d2d0329fd93e2eaca58d4a18d49fd05d","messageID":"msg_g001a087d70101001IbzxfkcSg","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":44503,"input":3121,"output":3750,"reasoning":0,"cache":{"write":0,"read":37632}},"cost":0}}
+{"type":"step_start","timestamp":1788985489568,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d8389e0012OASKkMX4","messageID":"msg_g001a087d80ad5001iluTkTzSf","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","snapshot":"3b320a092bc40276cce9a5f62cc9426d8d990064","type":"step-start"}}
+{"type":"text","timestamp":1788985496962,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d838ff0028acOFWWud","messageID":"msg_g001a087d80ad5001iluTkTzSf","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"text","text":"OUTWARD stage complete. Report written to `research/issue-310/outward.json`.\n\n**Search receipts (all real, this run):**\n- `Grep \"model_time|tool_time\"` — 51 hits repo-wide\n- `Grep \"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start\"` — 16 hits, all confined to definitions/docstring in `scripts/stage_telemetry.py`, test invocations in `tests/test_stage_telemetry.py:62-63,77`, and prior research artifacts — **zero call sites in `src/` and zero in `scripts/` outside the module itself**\n- `Grep \"StageAttempt|stage_telemetry\"` — 47 hits; sole production importer is `scripts/research_stage_executor.py:87-91`\n- `Grep \"ResearchEventRelay|elapsed\"` in executor — 20 hits; 5 relay invocations, only `elapsed` extracted\n- Full reads: `scripts/stage_telemetry.py` (1-221), `research_stage_executor.py` (60-129), `test_stage_telemetry.py` (50-109)\n\n**Sources classified:**\n- **O1** `scripts/stage_telemetry.py` — PRIMARY (StageAttempt: 4 marker pairs, `summary()` derives `model_time_s`/`tool_time_s` from summed windows, stage_telemetry.py:83-143)\n- **O2** `scripts/research_stage_executor.py:87-101` — PRIMARY (constructs StageAttempt, never calls any `mark_*` between line 89 and `finish()` at line 96)\n- **O3** `tests/test_stage_telemetry.py` — TEST_ONLY (only invocation site in the repo)\n- **O4** `research/issue-310/telemetry/attempts.jsonl` — EMPIRICAL (all three attempts incl. the 315s OUTWARD one show `model_time_s=0`, `tool_time_s=0`, `window_counts` all 0)\n- **O5** `inference_trace.py:69` / `rune_operator.py:1574` — DISTINCT-SCHEMA (`InferenceTrace.model_time_ms` works, easily conflated with StageAttempt's zeroed fields)\n- **O6** executor stage bodies — ADJACENT (mimo subprocess via relay; only coarse `elapsed` captured)\n\n**Evidence:** 7 claims (E1–E7) extracted. Static and empirical evidence agree with no contradictions; the one near-contradiction (`model_time` populated vs. zero) is resolved as two different pipelines. Limitations noted: relay internals not traced further (grep-verified no telemetry references), TIMEOUT status mapping untraced (out of B1 scope). No synthesis, no solution design, no code modified.","time":{"start":1788985489663,"end":1788985496961}}}
+{"type":"step_finish","timestamp":1788985496985,"sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","part":{"id":"prt_g001a087d85582001R1qSQSSAm","reason":"stop","snapshot":"1b3c3384c228d08690710336c599ea6de26144c8","messageID":"msg_g001a087d80ad5001iluTkTzSf","sessionID":"ses_-ffe5f782a30b9ffeXheAHMyyt","type":"step-finish","tokens":{"total":44247,"input":2852,"output":627,"reasoning":0,"cache":{"write":0,"read":40768}},"cost":0}}
@@ -0,0 +1,241 @@
+{
+  "issue": 310,
+  "round": 1,
+  "current_stage": "OUTWARD",
+  "completed_stages": [
+    "ISSUE",
+    "INWARD"
+  ],
+  "artifacts": {
+    "ISSUE": {
+      "contract": {
+        "issue": 310,
+        "title": "ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \u2014 model_time/tool_time always 0",
+        "question_type": "repo-specific",
+        "sub_questions": [
+          "Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \u2014 model_time/tool_time always 0"
+        ],
+        "required_stages": [
+          "ISSUE",
+          "INWARD",
+          "SYNTHESIS",
+          "QUALIFY"
+        ],
+        "skipped_stages": {
+          "ADVERSARIAL": "No design choice requiring adversarial evaluation.",
+          "APPLICABILITY": "No OUTWARD research to ground against Rune.",
+          "INNOVATION": "STANDARD_SOLUTION_SUFFICIENT \u2014 INNOVATION is conditional, not ceremonial.",
+          "OUTWARD": "No external factual uncertainty identified in the issue."
+        },
+        "evidence_classes": [
+          "repo"
+        ],
+        "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+        "expected_artifact": "synthesis.json",
+        "ambiguous": false,
+        "needs_mimo": false,
+        "source": "deterministic"
+      },
+      "deterministic": true
+    },
+    "INWARD": {
+      "context": {
+        "keywords": [
+          "adapt",
+          "local",
+          "like",
+          "telemetry",
+          "markers",
+          "never",
+          "invoked",
+          "production",
+          "path",
+          "model_time",
+          "tool_time",
+          "always",
+          "pre",
+          "registered",
+          "adapt",
+          "baseline",
+          "task",
+          "baseline",
+          "master",
+          "expected"
+        ],
+        "umbrella_matches": [
+          {
+            "umbrella": "memory",
+            "module": "drift_compression",
+            "keyword": "pre"
+          },
+          {
+            "umbrella": "perception",
+            "module": "context_pressure",
+            "keyword": "pre"
+          },
+          {
+            "umbrella": "perception",
+            "module": "auto_tasks",
+            "keyword": "task"
+          },
+          {
+            "umbrella": "capability",
+            "module": "local_tool_runtime",
+            "keyword": "local"
+          },
+          {
+            "umbrella": "inference",
+            "module": "response_adapter",
+            "keyword": "adapt"
+          },
+          {
+            "umbrella": "orchestration",
+            "module": "task_gate",
+            "keyword": "task"
+          },
+          {
+            "umbrella": "orchestration",
+            "module": "task_persist",
+            "keyword": "task"
+          }
+        ],
+        "candidate_files": [
+          "src/rune/rune_operator.py",
+          "src/rune/elastic_cognition.py",
+          "src/rune/growth_delta.py",
+          "src/rune/persona_gate.py",
+          "src/rune/rune_tui.py",
+          "src/rune/canary_p0_07.py",
+          "src/rune/canary_p1_02.py",
+          "src/rune/canary_p1_06.py",
+          "src/rune/capability_broker.py",
+          "src/rune/claim_audit.py",
+          "src/rune/contracts.py",
+          "src/rune/memory_selector.py",
+          "src/rune/memory_store.py",
+          "src/rune/model_routing.py",
+          "src/rune/canary_context_broker.py"
+        ],
+        "candidate_tests": [
+          "tests/test_p1_01_capability_authority.py",
+          "tests/test_p1_06_model_routing.py",
+          "tests/test_pipeline_integration.py",
+          "tests/test_p1_03_memory_selection.py",
+          "tests/test_p0_07_inference_trace.py",
+          "tests/test_p1_02_capsule_authority.py",
+          "tests/test_retrieval_benchmark.py",
+          "tests/test_adapt9_artifact_authority.py",
+          "tests/test_failure_auto_filer_task2.py",
+          "tests/test_research_sweep.py"
+        ],
+        "define_contract": {
+          "issue": 310,
+          "title": "ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \u2014 model_time/tool_time always 0",
+          "question_type": "repo-specific",
+          "sub_questions": [
+            "Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \u2014 model_time/tool_time always 0"
+          ],
+          "required_stages": [
+            "ISSUE",
+            "INWARD",
+            "SYNTHESIS",
+            "QUALIFY"
+          ],
+          "skipped_stages": {
+            "ADVERSARIAL": "No design choice requiring adversarial evaluation.",
+            "APPLICABILITY": "No OUTWARD research to ground against Rune.",
+            "INNOVATION": "STANDARD_SOLUTION_SUFFICIENT \u2014 INNOVATION is conditional, not ceremonial.",
+            "OUTWARD": "No external factual uncertainty identified in the issue."
+          },
+          "evidence_classes": [
+            "repo"
+          ],
+          "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+          "expected_artifact": "synthesis.json",
+          "ambiguous": false,
+          "needs_mimo": false,
+          "source": "deterministic"
+        },
+        "mimo_needed": false
+      },
+      "deterministic": true,
+      "claims": [
+        {
+          "id": "I1",
+          "claim": "Relevant file: src/rune/rune_operator.py",
+          "evidence": [
+            "src/rune/rune_operator.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I2",
+          "claim": "Relevant file: src/rune/elastic_cognition.py",
+          "evidence": [
+            "src/rune/elastic_cognition.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I3",
+          "claim": "Relevant file: src/rune/growth_delta.py",
+          "evidence": [
+            "src/rune/growth_delta.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I4",
+          "claim": "Relevant file: src/rune/persona_gate.py",
+          "evidence": [
+            "src/rune/persona_gate.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I5",
+          "claim": "Relevant file: src/rune/rune_tui.py",
+          "evidence": [
+            "src/rune/rune_tui.py"
+          ],
+          "status": "CURRENT"
+        }
+      ]
+    }
+  },
+  "blocking_unknowns": [],
+  "status": "ACTIVE",
+  "stage_history": [
+    {
+      "stage": "ISSUE",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "contract",
+        "deterministic"
+      ]
+    },
+    {
+      "stage": "INWARD",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "context",
+        "deterministic",
+        "claims"
+      ]
+    },
+    {
+      "stage": "OUTWARD",
+      "round": 1,
+      "failed": true,
+      "reason": "OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \u2014 search snippets alone do not count as evidence"
+    },
+    {
+      "stage": "OUTWARD",
+      "round": 1,
+      "failed": true,
+      "reason": "OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \u2014 search snippets alone do not count as evidence"
+    }
+  ]
+}
@@ -0,0 +1,4 @@
+{"attempt_id": "issue-310-ISSUE-1-a1", "event_id": "issue-310-ISSUE-1", "stage": "ISSUE", "issue": 310, "process_id": "research-310-r1", "started_at": "2026-09-09T20:15:09.949030+00:00", "finished_at": "2026-09-09T20:15:10.108621+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.1597, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-310-INWARD-1-a1", "event_id": "issue-310-INWARD-1", "stage": "INWARD", "issue": 310, "process_id": "research-310-r1", "started_at": "2026-09-09T20:15:34.792311+00:00", "finished_at": "2026-09-09T20:15:35.016831+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.2246, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-310-OUTWARD-1-a1", "event_id": "issue-310-OUTWARD-1", "stage": "OUTWARD", "issue": 310, "process_id": "research-310-r1", "started_at": "2026-09-09T20:16:01.999099+00:00", "finished_at": "2026-09-09T20:21:17.061293+00:00", "terminal_status": "GATE_FAILED", "wall_time_s": 315.0622, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-310-OUTWARD-2-a2", "event_id": "issue-310-OUTWARD-2", "stage": "OUTWARD", "issue": 310, "process_id": "research-310-r1", "started_at": "2026-09-09T20:22:10.283396+00:00", "finished_at": "2026-09-09T20:27:01.337302+00:00", "terminal_status": "GATE_FAILED", "wall_time_s": 291.0539, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
@@ -0,0 +1 @@
+consumed at 1788985684.7973979
@@ -0,0 +1 @@
+consumed at 1788985684.6077118
@@ -0,0 +1 @@
+consumed at 1788985705.7648733
@@ -0,0 +1,192 @@
+{
+  "stage": "OUTWARD",
+  "issue": 311,
+  "round": 1,
+  "attempt": 1,
+  "subquestion": "Address: ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)",
+  "required_source_classes": ["repo", "external"],
+  "queries": [
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "architecture report generated from import graph \"no hand-maintained\" dependency diagram CI",
+      "result": "0 results (search engine returned empty SERP)",
+      "receipt": "webfetch 200, SERP text 'No results found for ...' — recorded as-is; topic covered by narrower queries below"
+    },
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "import-linter enforce architecture layers python contract",
+      "result": "10 hits",
+      "receipt": "webfetch 200; hits included import-linter.readthedocs.io contract_types/layers/, github.com/seddonym/import-linter, pypi.org/project/import-linter (published 2026-09-04), roman.pt/posts/python-architecture-linter/, matthiaseg.github.io ADR-0001"
+    },
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "pytest architectural fitness functions dependency rules plugin",
+      "result": "10 hits",
+      "receipt": "webfetch 200; hits included github.com/LukasNiessen/ArchUnitPython, pypi.org/project/PyTestArch/, deepwiki.com/jwbargsten/pytest-archon, andi-john-dev.de/blog/python-architecture-rules-with-pytestarch (2026-04-28)"
+    },
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "madge dependency-cruiser visualize module dependencies report",
+      "result": "10 hits",
+      "receipt": "webfetch 200; hits included github.com/pahen/madge, www.npmjs.com/package/dependency-cruiser (v18.1.1), densitylabs.io madge walkthrough"
+    },
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "vulture dead code python static analysis unreferenced",
+      "result": "10 hits",
+      "receipt": "webfetch 200; hits included github.com/jendrikseipp/vulture, pypi.org/project/vulture/, stackoverflow.com/questions/693070"
+    },
+    {
+      "kind": "SEARCH",
+      "tool": "webfetch DuckDuckGo HTML SERP",
+      "query": "ArchUnit architecture test freeze violations report",
+      "result": "10 hits",
+      "receipt": "webfetch 200; hits included www.archunit.org/userguide/html/000_Index.html, github.com/TNG/ArchUnit, deepwiki Freezing Architecture Rules page, codecentric.de ArchUnit-in-practice"
+    }
+  ],
+  "sources": [
+    {
+      "id": "O1",
+      "url": "https://github.com/seddonym/import-linter",
+      "classification": "OFFICIAL_DOCS (project README, Python)",
+      "selected_for_reading": true,
+      "read_receipt": "webfetch 200 of https://raw.githubusercontent.com/seddonym/import-linter/main/README.md (first attempt .../README.rst returned 404; retried .md successfully)"
+    },
+    {
+      "id": "O2",
+      "url": "https://import-linter.readthedocs.io/en/stable/contract_types/layers/",
+      "classification": "OFFICIAL_DOCS (Layers contract type)",
+      "selected_for_reading": false,
+      "read_receipt": "SERP snippet only (README read instead covers the tool's contract surface)"
+    },
+    {
+      "id": "O3",
+      "url": "https://pypi.org/project/PyTestArch/",
+      "classification": "REGISTRY (Python pytest architecture-rule library)",
+      "selected_for_reading": false,
+      "read_receipt": "SERP snippet only"
+    },
+    {
+      "id": "O4",
+      "url": "https://github.com/sverweij/dependency-cruiser",
+      "classification": "OFFICIAL_DOCS (project README, JS/TS)",
+      "selected_for_reading": true,
+      "read_receipt": "webfetch 200 of https://raw.githubusercontent.com/sverweij/dependency-cruiser/main/README.md"
+    },
+    {
+      "id": "O5",
+      "url": "https://github.com/jendrikseipp/vulture",
+      "classification": "OFFICIAL_DOCS (project README, Python dead-code finder)",
+      "selected_for_reading": true,
+      "read_receipt": "webfetch 200 of https://raw.githubusercontent.com/jendrikseipp/vulture/main/README.md"
+    },
+    {
+      "id": "O6",
+      "url": "https://www.archunit.org/userguide/html/000_Index.html",
+      "classification": "OFFICIAL_DOCS (ArchUnit 1.5.0 user guide, Java)",
+      "selected_for_reading": true,
+      "read_receipt": "webfetch 200 (large page; head+tail captured, middle truncated at ~1114 lines — frozen-rules section read via SERP/DeepWiki snippet corroboration)"
+    },
+    {
+      "id": "R1",
+      "path": "/mnt/workdrive/rune/config/v1_authority_map.json",
+      "classification": "REPO_ARTIFACT (authority map data source named by issue #311)",
+      "selected_for_reading": true,
+      "read_receipt": "file exists (26,538 bytes, mtime 2026-09-08); top-level keys: schema_version, status ('decision-record-not-migration'), epic (#16), issue (#17), frozen_reference (tag v0.42.0, commit 98b8a70...), v1_branch, invariant, dispositions, responsibilities"
+    },
+    {
+      "id": "R2",
+      "path": "/mnt/workdrive/rune/scripts/gen_prd_state.py",
+      "classification": "REPO_PATTERN (generated-state report, the 'PRD state generator' pattern cited by issue #311)",
+      "selected_for_reading": true,
+      "read_receipt": "grep receipts: def version() :29, def git_head() :35, def pipeline_state() :44, def tui_state() :100 ('### TUI-adjacent subsystems (impact map)' :115), def regenerate(path, new_state) :129, def main :146; module docstring: PRD 'current state' sections are GENERATED from governed sources (config/umbrellas.json, pipeline/TUI state) while doctrine sections are hand-written"
+    },
+    {
+      "id": "R3",
+      "path": "/mnt/workdrive/rune/src/rune/orchestration/benchmark.py",
+      "classification": "REPO_PATTERN (orchestration reporting pattern cited by issue #311)",
+      "selected_for_reading": true,
+      "read_receipt": "grep receipts: def fingerprint() :22, def run_batches() :40, def p95() :51, def evaluate_p95_regression() :57"
+    },
+    {
+      "id": "R4",
+      "path": "/mnt/workdrive/rune/scripts/ (whole dir) + repo-wide grep",
+      "classification": "REPO_PATTERN (claimed 'module scan / walkman pattern' named by issue #311)",
+      "selected_for_reading": true,
+      "read_receipt": "ls scripts/ = 19 files (auto_bump_pr.py, capture_failure.py, gen_prd_state.py, lint_ratchet.py, type_check_ratchet.py, umbrella_impact.py, ...); repo-wide grep -i 'walkman' over src/, scripts/, docs/ AND harness repo returned ZERO hits; closest existing module-scan tooling = capture_failure.py (fixture capture) and umbrella_impact.py; no AST-based import-graph scanner exists in scripts/"
+    }
+  ],
+  "evidence": [
+    {
+      "id": "E1",
+      "source": "O1",
+      "claim": "import-linter (Python, BSD-2, actively published 2026-09-04) analyzes import relationships between modules and checks them against user-declared contracts; it additionally 'provides a browser-based user interface for exploring the architecture of any Python package' — i.e. mature tooling treats the import graph as the machine-checkable source of architecture truth, with contracts (layers/forbidden/independence) as the declarative layer on top.",
+      "locus": "README.md; corroborated by SERP hit roman.pt/posts/python-architecture-linter/ ('in a config file, you define so-called contracts')"
+    },
+    {
+      "id": "E2",
+      "source": "O4",
+      "claim": "dependency-cruiser 'runs through the dependencies in any JS/TS project and validates them against your own rules, reports violated rules in text (for your builds) and in graphics (for your eyeballs)'; default init rules include orphans and circular dependencies; output types include dot, mermaid, json, csv, html, text; it 'uses itself to check on itself in its own build process'. Key shape for #158: ONE engine emits BOTH a machine-consumable validation report AND a human status/graph view from the same scan.",
+      "locus": "README.md sections 'What's this do?', 'Validate things', 'Report them', package.json depcruise script reference"
+    },
+    {
+      "id": "E3",
+      "source": "O5",
+      "claim": "vulture finds unused Python code via AST analysis, assigning confidence values per code type (unreachable code 100%, imports 90%, attributes/functions/variables 60%) and supports --min-confidence, whitelists, and programmatic use (v.scavenge([...]); v.get_unused_code() -> Item objects). Directly relevant to #158's 'identifies a deliberately disconnected test subsystem as not-live': liveness claims about unreferenced modules are inherently probabilistic and need a confidence/whitelist mechanism — 'code that is only called implicitly may be reported as unused' (dynamic dispatch, registries, hooks).",
+      "locus": "README.md sections 'Types of unused code' (confidence table), 'Handling false positives', 'How does it work?', 'Integrations' (programmatic API)"
+    },
+    {
+      "id": "E4",
+      "source": "O6",
+      "claim": "ArchUnit's established pattern: import the code graph (ClassFileImporter), evaluate rules as tests, report violations with exact class+line; FreezingArchRule stores known violations in a frozen file so legacy violations don't block adoption and auto-shrinks as violations are fixed (regression protection). The 'architecture as test' pattern is language-portable (Python ports ArchUnitPython, PyTestArch, pytest-archon exist — O3/SERP). #158's report table maps onto this: Defined/Live-caller/Causal-path columns are exactly the predicates such rules evaluate.",
+      "locus": "ArchUnit User Guide 1.5.0 sections 3.2, 5.2, 7.1; freeze mechanism corroborated by DeepWiki 'Freezing Architecture Rules' + codecentric.de ('Thanks to the freeze function violations can be fixed step by step')"
+    },
+    {
+      "id": "E5",
+      "source": "R1",
+      "claim": "config/v1_authority_map.json exists as named by issue #311 and already carries governed, machine-readable authority data (schema_version, status='decision-record-not-migration', invariant, dispositions, responsibilities) — a report generator can consume it directly as the authority-coverage column source rather than inventing a new registry.",
+      "locus": "file top-level keys; 26.5 KB"
+    },
+    {
+      "id": "E6",
+      "source": "R2",
+      "claim": "Rune already has an in-house generated-truth-report precedent with the exact epistemic split #158 needs: gen_prd_state.py regenerates the PRDs' 'current state' sections FROM governed sources (config/umbrellas.json, pipeline/TUI state) while leaving doctrine sections hand-written, and it includes a subsystem 'impact map' section; regenerate() handles the write-back idempotently.",
+      "locus": "gen_prd_state.py docstring + def pipeline_state :44, def tui_state :100, def regenerate :129"
+    },
+    {
+      "id": "E7",
+      "source": "R3",
+      "claim": "The orchestration reporting pattern cited by the issue exists: orchestration/benchmark.py provides fingerprint() (run provenance), p95(), and evaluate_p95_regression() — i.e. deterministic evaluation helpers a wiring report's CI/test integration can reuse for its own 'regenerable deterministically' acceptance criterion.",
+      "locus": "benchmark.py:22,40,51,57"
+    },
+    {
+      "id": "E8",
+      "source": "R4",
+      "claim": "CONTRADICTION with issue #311's dependency list: the claimed 'module scan (walkman pattern exists)' does NOT exist — zero grep hits for 'walkman' anywhere in /mnt/workdrive/rune (src/, scripts/, docs/, all file types) or the harness repo. The dependency named in the issue is stale or refers to an unmerged/renamed artifact; the design contract must not assume it.",
+      "locus": "grep receipts recorded in R4"
+    }
+  ],
+  "limitations": [
+    "External evidence is tooling-pattern evidence (import-graph linters, dead-code finders, architecture-test frameworks); no source describes a 'wiring-status report' combining import graph + authority-map coverage in one table — the specific #158 artifact shape appears to be novel to Rune, so cross-tool comparison covers components, not the composite.",
+    "ArchUnit user guide (O6) was fetched but the page is very large; the freeze section was captured only via head/tail + SERP/DeepWiki corroboration, not the full in-page text.",
+    "Liveness detection evidence (O5) is Python-static-analysis-specific; Rune's actual dynamic dispatch surface (hook_engine, capability_broker, plugin-style registration) may need registry-aware liveness rules none of the read sources directly address — flagged as an unresolved design input for later stages.",
+    "O2 (import-linter layers contract docs), O3 (PyTestArch), and the madge README were discovered and classified but NOT read in full; their evidence here is SERP-snippet-level and should not be cited beyond classification.",
+    "Repo-side receipts (R1–R4) are grep/ls/file-level, not full-file reads; line numbers come from grep -n output."
+  ],
+  "contradictions": [
+    "E8 vs issue #311 text: issue names 'module scan (walkman pattern exists)' as a known dependency; repo-wide grep finds no 'walkman' anything. Either the issue text is stale or the pattern lives outside this working tree.",
+    "None otherwise: O1/O4/O6/E5–E7 are mutually consistent — machine-generated architecture truth from the import graph + registries, with declarative contracts/rules layered on, is the converged industry pattern."
+  ],
+  "supporting_evidence_count": 8,
+  "unresolved_questions": [
+    "What defines 'live caller / causal path' for Rune subsystems that are wired via registries, hooks, or dynamic dispatch (where static import analysis alone would falsely report not-live — E3's whitelist/confidence problem)?",
+    "Should the report validate (test-style, ArchUnit/dependency-cruiser pattern, E2/E4) or only report (status view), or both from one engine as dependency-cruiser does?",
+    "Is v1_authority_map.json (R1) the single authority-coverage source, or do other registries (config/umbrellas.json per E6) also belong in the coverage column?"
+  ],
+  "next_stage_hint": "ADVERSARIAL should attack: (a) static-import-only liveness vs Rune's dynamic wiring (false not-live reports — E3 false-positive evidence); (b) the stale 'walkman' dependency claim (E8) if the design contract leans on it; (c) determinism of any report that embeds timestamps/graph layout."
+}
@@ -0,0 +1,144 @@
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+{"type":"text","timestamp":1788985734050,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dbed550020POtxEwJb","messageID":"msg_g001a087db8b68001avauCXHQy","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"I'll start with the required skill search and check project memory for context on Issue #311 / #158 / ADAPT-1 B2.","time":{"start":1788985732437,"end":1788985734047}}}
+{"type":"tool_use","timestamp":1788985734054,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"skill_search","callID":"call_bf531b3ec76742568f640e7e","state":{"status":"completed","input":{"query":"Discover and classify candidate external web sources for a research question about a wiring-status/architecture-truth report generator feature; perform real web searches, record source IDs and fetch receipts, extract evidence claims, produce an evidence report. Audience: engineering research pipeline."},"output":"{\n  \"status\": \"matched\",\n  \"results\": [\n    {\n      \"skill_id\": \"firecrawl-search\",\n      \"name\": \"firecrawl-search\",\n      \"score\": 0.6224,\n      \"reason\": \"The skill description matches these query terms: discover, web, source, research, about, real.\"\n    },\n    {\n      \"skill_id\": \"super-research\",\n      \"name\": \"super-research\",\n      \"score\": 0.5326,\n      \"reason\": \"The skill description matches these query terms: candidate, external, source, research, question, about, real, record, evidence, produce.\"\n    },\n    {\n      \"skill_id\": \"firecrawl\",\n      \"name\": \"firecrawl\",\n      \"score\": 0.4664,\n      \"reason\": \"The skill description matches these query terms: external, web, research, real, fetch.\"\n    }\n  ],\n  \"loaded_skill_id\": null\n}","metadata":{"status":"matched","loadedSkillID":null,"truncated":false},"title":"Found 3 skills","time":{"start":1788985734049,"end":1788985734052}},"id":"prt_g001a087dbed5b001TFQBYAgIb","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087db8b68001avauCXHQy"}}
+{"type":"tool_use","timestamp":1788985734237,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"memory","callID":"call_3b97b2ea418743a185f89ebd","state":{"status":"completed","input":{"operation":"search","query":"ADAPT-1 wiring-status architecture-truth report generator"},"output":"Found 10 matches (BM25-ranked, best first).\nA hit here is authoritative — use it even if a parallel/sibling query returned nothing.\nIf you need the FULL body (snippets are truncated), Read the path.\nIf you need an EXACT literal (a connection string, port, token, full command line, path) and the snippet/body only paraphrases or partially shows it, the curated memory may have dropped the precise form — query the history tool for the original message, which holds it verbatim.\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD/checkpoint-pipeline-stage-specs.md\nScope: sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD, Type: checkpoint, Score: 10.663\n...25. **<<Report>>**: update `~/Desktop/RUNE_RESEARCHPROCESS_RATIFICATION_<<REPORT>>.md` with the canonical responsibility table (PI/GITEA, DESKTOP RUNNER, RUNE BACKEND, MIMO CODE, HENXELS/GATES, GITEA TRANSITION LOGIC); <<status>> EXPERIMENTAL until one real...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD/checkpoint.md\nScope: sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD, Type: checkpoint, Score: 10.011\n...<<1>>), file channel primary (→<<ADAPT>>-9). REMOVE: nothing further.\n\nClosing doctrine (verbatim, cumulative): \"A REPLACEMENT IS NOT COMPLETE WHILE THE OLD AUTHORITY CAN STILL QUIETLY RUN.\" / \"ADDITION WITHOUT RETIREMENT CREATES GHOST <<ARCHITECTURE>>...\n\n### /home/nick/.local/share/mimocode/memory/projects/global/MEMORY.md\nScope: projects/global, Type: memory, Score: 8.266\n...verified live; <<report>> at ~/Desktop/RUNE_<<ARCHITECTURE>>_INTEGRITY_<<REPORT>>.md. P0-B/C/D/E DEFERRED.\n- **FEATURE-CLOBBER 3 INSTANCES (2026-09-08):** #210 tui_validator, #212 umbrella-<<wiring>>, #242 canary-contract...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5fcf0fa7e9ffe73c5cHWhL/tui_build_ledger.md\nScope: sessions/ses_-ffe5fcf0fa7e9ffe73c5cHWhL, Type: free, Score: 7.056\n...Source of <<truth>> for build progress._\n_TUI is at: /mnt/workdrive/rune/src/rune/_\n_<<Wiring>> is mandatory: standalone scripts = not done._\n\n## Pre-build Checklist\n- [x] Deep research complete (27 papers, source links...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5fcf0fa7e9ffe73c5cHWhL/build_ledger.md\nScope: sessions/ses_-ffe5fcf0fa7e9ffe73c5cHWhL, Type: free, Score: 6.976\n...Source of <<truth>> for build progress._\n_Backups at: ~/.config/opencode/backups/drift-build-20260824/_\n_<<Wiring>> is mandatory: standalone scripts = not done._\n\n## Pre-build Checklist\n- [x] Deep research complete (27 papers, source links...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f98e46b46ffe7fdgz483s/checkpoint.md\nScope: sessions/ses_-ffe5f98e46b46ffe7fdgz483s, Type: checkpoint, Score: 6.925\n...New issues: **#155** (P1 activation/execution trace — #35 prerequisite), **#156** (P1 mutation guards), **#157** (P1 failure→fixture), **#158** (P2 <<wiring>>-<<truth>> <<report>>), **#159** (P3 adaptive concepts — Nick's design; gated on #33...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_fdfd9d8feffeq4KFcaRIVNGF9N/checkpoint.md\nScope: sessions/ses_fdfd9d8feffeq4KFcaRIVNGF9N, Type: checkpoint, Score: 6.890\n...Microkernel plugin <<architecture>> — minimal dispatch engine, self-registering plugins, hook-based events, persona authority\n_Generated by checkpoint writer; structure preserved across updates. Edit only content under italic instructions._\n\n## §<<1>> Active intent\n_User...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a28a2ecffeEs822F6Ir/checkpoint.md\nScope: sessions/ses_-ffe5f7a28a2ecffeEs822F6Ir, Type: checkpoint, Score: 6.736\n...md ## <<Architecture>> decisions when proven cross-session-durable._\n\n- (pending artifact) Working disposition for innovation.json, based on verified evidence: conclusion likely <<ADAPT>>, with candidates — C5 as <<ADAPT>> (NEP-001 Phase-<<1>> AS...\n\n### /home/nick/.local/share/mimocode/memory/projects/global/MEMORY-environment-doctrine-2026-09-06.md\nScope: projects/global, Type: memory, Score: 6.482\n...181 + #182 (GitHub code-search ADOPT/<<ADAPT>>/BORROW/BUILD) + #183 (typed temporal semantics); #161 carries two addenda (canonical-authority contract + extended bake-off dimensions, \"simplest <<architecture>> that measurably wins\"). All P3 — low...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5fdce6835cffezTlUd3Fwd/checkpoint.md\nScope: sessions/ses_-ffe5fdce6835cffezTlUd3Fwd, Type: checkpoint, Score: 6.448\n...Pushed v0.8.0 + v0.8.<<1>>.\n\n### Self-iteration loop — COMPLETE\n\n- ✅ All pins closed. Cache <<wiring>>. Abstraction pipeline. RuneBench 30→Line truncated
+{"type":"tool_use","timestamp":1788985734329,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"memory","callID":"call_c2fe52d584af4f7a92071325","state":{"status":"completed","input":{"operation":"search","query":"issue 311 outward research stage"},"output":"Found 10 matches (BM25-ranked, best first).\nA hit here is authoritative — use it even if a parallel/sibling query returned nothing.\nIf you need the FULL body (snippets are truncated), Read the path.\nIf you need an EXACT literal (a connection string, port, token, full command line, path) and the snippet/body only paraphrases or partially shows it, the curated memory may have dropped the precise form — query the history tool for the original message, which holds it verbatim.\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c/checkpoint.md\nScope: sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c, Type: checkpoint, Score: 7.781\n...<<OUTWARD>> artifact must be recorded here when done.\n- `/mnt/workdrive/<<research>>-<<stage>>/<<research>>/<<issue>>-263/runs/` — per-run directory for <<stage>> artifacts.\n- `/mnt/workdrive/<<research>>-<<stage>>/prompts/<<research>>-stages/<<outward>>.md` — the...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG/checkpoint.md\nScope: sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG, Type: checkpoint, Score: 7.718\n...List with one-line purpose._\n\n- `/mnt/workdrive/<<research>>-<<stage>>/<<research>>/<<issue>>-161/task_tree.json` — round state; <<ISSUE>>+INWARD done, <<OUTWARD>> next\n- `/mnt/workdrive/<<research>>-<<stage>>/<<research>>/<<issue>>-263/<<outward>>.json` — artifact...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR/checkpoint.md\nScope: sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR, Type: checkpoint, Score: 7.633\n...<<research>>/<<issue>>-310/<<outward>>.json (or <<stage>>-named <<OUTWARD>> artifact) ending `StageCompleted: <<OUTWARD>>`.\n- Untracked evidence receipts already on disk: <<research>>/<<issue>>-310/<<stage>>_<<OUTWARD>>.events.jsonl, <<research>>/<<issue>>-310/telemetry/attempts.jsonl...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1/checkpoint.md\nScope: sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1, Type: checkpoint, Score: 7.616\n...Read `<<research>>/<<issue>>-163/task_tree.json` → current_<<stage>> <<OUTWARD>>, completed [<<ISSUE>>, INWARD], status ACTIVE, no artifacts beyond <<ISSUE>> (deterministic contract; evidence bar: ≥2 unique URLs for <<OUTWARD>>) and INWARD (auto keyword...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB/checkpoint.md\nScope: sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB, Type: checkpoint, Score: 7.581\n...Read `<<research>>/<<issue>>-163/task_tree.json`: confirmed <<stage>> state (<<ISSUE>>, INWARD, <<OUTWARD>> complete; APPLICABILITY next) and INWARD claims I1–I5.\n\nNOT yet done: writing `<<research>>/<<issue>>-163/applicability.json`. The classification...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD/checkpoint-rp2-correction-265-outward-specs.md\nScope: sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD, Type: checkpoint, Score: 7.513\n...runner_hostname, runner_name, runner_labels, execution_class (desktop-heavy), <<stage>>, process_id, <<issue>>_id, <<research>>_process_id, timestamp. Example: runner_name = rune-ci-desktop, execution_class = desktop-heavy, <<stage>> = <<OUTWARD>>.\n- Negative...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f826d4b3affeptScH2iSt/notes.md\nScope: sessions/ses_-ffe5f826d4b3affeptScH2iSt, Type: free, Score: 7.442\n...NO DEFINE <<stage>>. The Gitea <<issue>> IS the <<research>> contract. <<Issue>> quality is checked deterministically.\n2. NEW PIPELINE: <<ISSUE>> → INWARD → <<OUTWARD>> → APPLICABILITY → INNOVATION? → ADVERSARIAL → SYNTHESIS → QUALIFY → PROCEED/REFINE\n3. <<OUTWARD>> is ONE...\n\n### /home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md\nScope: projects/add96ab3-25dd-4c38-9fa3-34c01811d081, Type: memory, Score: 7.406\n...at `/mnt/workdrive/issue161-harness/<<research>>/<<issue>>-163/task_tree.json` (NOT the <<research>>-<<stage>> repo — that older path doesn't apply to new rounds). <<OUTWARD>> accepted (attempt 2; first failed with...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cedfc3cffe4Jz3Ie6ag/checkpoint.md\nScope: sessions/ses_-ffe5f7cedfc3cffe4Jz3Ie6ag, Type: checkpoint, Score: 7.386\n...Located <<stage>> artifacts on disk: /mnt/workdrive/<<research>>-<<stage>>/<<research>>/<<issue>>-262/ contains <<outward>>_reading.json (SOURCES S1-S11, CLAIMS O1-O19, mapping_to_repo, limitations, next_<<stage>>_hint — read in full...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cd9dc19ffeh9xe8IpyD/checkpoint-handoff-digest.md\nScope: sessions/ses_-ffe5fLine truncated
+{"type":"step_finish","timestamp":1788985734574,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dbf4b9001AriYI524V","reason":"tool-calls","snapshot":"77fb7d2e8dfd0495295e9fa70ff928280a5a3db7","messageID":"msg_g001a087db8b68001avauCXHQy","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":28770,"input":28481,"output":289,"reasoning":0,"cache":{"write":0,"read":0}},"cost":0}}
+{"type":"step_start","timestamp":1788985750105,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc3257001jfMld0iBH","messageID":"msg_g001a087dbf6c6001i6M8UQKAI","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"5e592a19cde024e2c753be072782084c66fae5c1","type":"step-start"}}
+{"type":"text","timestamp":1788985751630,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc32e40019FMJz2r1r","messageID":"msg_g001a087dbf6c6001i6M8UQKAI","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"This is a Rune research-pipeline OUTWARD stage for Issue #311. Let me gather the issue context and locate the research workspace.","time":{"start":1788985750244,"end":1788985751627}}}
+{"type":"tool_use","timestamp":1788985751647,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"read","callID":"call_c157a6320a9d4679bb199f2f","state":{"status":"completed","input":{"file_path":"/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md"},"output":"<path>/home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md</path>\n<type>file</type>\n<content>\n1: # Memory spillover: pipeline history & completed early-stage artifacts\n2: _Extracted from MEMORY.md ## Discovered durable knowledge (token-budget extraction). Historical/completed content: pipeline conventions, stage techniques, grounding facts, and per-stage artifacts for issue-262 / issue-161 / issue-163 up through INNOVATION. Consult when working older rounds or needing source-level detail; the operative issue-163 constraints (ADVERSARIAL M1–M7/T1–T6, SYNTHESIS round-1, QUALIFY) remain in MEMORY.md._\n3: \n4: ## Entries\n5: \n6: - Rune research pipeline has 8 stages: DEFINE → INWARD → OUTWARD_DISCOVERY → OUTWARD_READING → ADVERSARIAL → INNOVATION → SYNTHESIS (+1 completion/validation stage). Dispatched headless via `.gitea/workflows/research-stage-headless.yml` (PRs #217/#218) + `run_agent_stage.py` (#222).\n7: - Research questions are filed in the Rune repo as `research/issue-<n>-research.md` (or under `/mnt/workdrive/rune/research/<topic>/` subdirectories). DEFINE-stage dispatches may reference \"the research question\" without restating it — locate the question file before classifying.\n8: - Stage-execution tree for research rounds lives at `/mnt/workdrive/research-stage/` (holds src/rune/ + research-executor commits, e.g. HEAD 83ea89c \"OUTWARD_DISCOVERY executor\"); distinct from the subject repo `/mnt/workdrive/rune/`.\n9: - OUTWARD_DISCOVERY technique that works here: plain webfetch of `https://duckduckgo.com/html/?q=<url-encoded query>` returns title+URL+snippet SERPs; batch ≥4 queries in parallel; snippet-level evidence satisfies the \"discover URLs, classify sources, don't read full sources\" stage contract.\n10: - OUTWARD_READING technique that works here: batch webfetch in parallel; GitHub repos read cleaner via `raw.githubusercontent.com/<owner>/<repo>/<branch>/README.md` (avoids page chrome); dev.to and sqliteforum.com (Substack-style) pages fetch OK but carry navigation noise around mid-page content; extracted claims go in a session spillover file (e.g. `checkpoint-outward-reading-sources.md`) with S-numbered source IDs so the ADVERSARIAL stage can reference claims.\n11: - Rune's SQLite usage (grounding for DB-related research questions): ~15 modules in src/rune/ each open fresh short-lived sqlite3 connections per call against a shared STORE_DB (mix of RW and `file:...?mode=ro` URI reads) across multiple OS processes; only task_gate.py sets `PRAGMA journal_mode=WAL` explicitly; sqlite-vec extension must be loaded per connection (issue #26 defect fix).\n12: - Newer pipeline runs use a 7-stage pipeline with a UNIFIED OUTWARD stage (discovery + reading merged, O-numbered source IDs, artifact ends `StageCompleted: OUTWARD`); the older 8-stage split (OUTWARD_DISCOVERY → OUTWARD_READING, S-numbered IDs) still applies to older rounds like issue-262. Deterministic DEFINE contracts may mark sub-stages \"skipped\" while the unified stage still requires \"≥2 unique URLs\".\n13: - Rune's memory stack (grounding for issue-161 OUTWARD): sqlite-vec (dense vectors) + FTS5 (BM25) in one SQLite file (`src/rune/memory_store.py`), hybrid recall accelerated by a precomputed association graph (hops=1); separate headless SQLite graph tier at `memory/graph/graph.sqlite` (`src/rune/graph_memory.py`); no Qdrant dependency exists — the \"vs Qdrant vs graph backends\" part of the question is comparative research, not existing code.\n14: - Issue-262 round already researched SQLite WAL + concurrency (artifact at `research/issue-262/outward.json` + `.firecrawl/` source snapshots); don't re-research WAL in memory-backend rounds.\n15: - Issue-161 round 1 (memory backend abstraction + comparative benchmark harness): ADVERSARIAL settled SURVIVES_WITH_MITIGATIONS. Survivors: sqlite-hybrid-retrieval, retrieval-quality-metrics-suite, reproducibility-contract, matched-precision-comparison-methodology, candidate-pool-vs-ranking-diagnostic, substrate-family-comparative-eval. memory-adapter-protocol REJECTED as duplicate authority — memory_selector.py's source registry (add_source()/DEFAULT_SOURCES, memory_selector.py:130-133 & 504-511, contract `(query, types, budget, min_score) -> list[dict]`) already IS the backend abstraction; do NOT resurrect it (mitigation M5). SYNTHESIS must carry mitigations M1–M10 and convert falsification tests FT1–FT7 into invariants/tests (full text in the SYNTHESIS dispatch and stage artifacts at `/mnt/workdrive/research-stage/research/issue-161/`; expected artifact `researLine truncated
+{"type":"tool_use","timestamp":1788985751699,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_2e03be522f0540e4b85f95f4","state":{"status":"completed","input":{"command":"ls /mnt/workdrive/ 2>/dev/null; ls /mnt/workdrive/research-stage/research/ 2>/dev/null | tail -30","description":"List workdrive and research issue dirs"},"output":"Bottles\ncoding\nissue161-harness\nMusic Journalism\nMusic Production\np1-03\np122\np149\np150\np151\np192\nprobot\nprun\nReaper Projects\nRed Giant\nresearch-stage\nrobot-fix\nrune\nscarlett config\nSteamLibrary\nStudio One Projects\nVideo Projects\nwine-ni\nbatch-processing\nbuild-mode\ncontract-testing\nfull-audit\ninterstitial-tools\nissue-161\nissue-245-research.md\nissue-260\nissue-261\nissue-262\nissue-263\nllm-craft-api\nllm-craft-deep\nquality-tools\nresearch-methodology\nrune-efficiency\nsafety-override\ntextual-craft\ntool-calling\nuncensored-models\nv1\nworkflow-audit\n","metadata":{"output":"Bottles\ncoding\nissue161-harness\nMusic Journalism\nMusic Production\np1-03\np122\np149\np150\np151\np192\nprobot\nprun\nReaper Projects\nRed Giant\nresearch-stage\nrobot-fix\nrune\nscarlett config\nSteamLibrary\nStudio One Projects\nVideo Projects\nwine-ni\nbatch-processing\nbuild-mode\ncontract-testing\nfull-audit\ninterstitial-tools\nissue-161\nissue-245-research.md\nissue-260\nissue-261\nissue-262\nissue-263\nllm-craft-api\nllm-craft-deep\nquality-tools\nresearch-methodology\nrune-efficiency\nsafety-override\ntextual-craft\ntool-calling\nuncensored-models\nv1\nworkflow-audit\n","exit":0,"description":"List workdrive and research issue dirs","truncated":false},"title":"List workdrive and research issue dirs","time":{"start":1788985751681,"end":1788985751697}},"id":"prt_g001a087dc350a001Wh0K1iHtM","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dbf6c6001i6M8UQKAI"}}
+{"type":"tool_use","timestamp":1788985751720,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"memory","callID":"call_31709926511642aca5896e54","state":{"status":"completed","input":{"operation":"search","query":"issue-311"},"output":"Found 10 matches (BM25-ranked, best first).\nA hit here is authoritative — use it even if a parallel/sibling query returned nothing.\nIf you need the FULL body (snippets are truncated), Read the path.\nIf you need an EXACT literal (a connection string, port, token, full command line, path) and the snippet/body only paraphrases or partially shows it, the curated memory may have dropped the precise form — query the history tool for the original message, which holds it verbatim.\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB/checkpoint.md\nScope: sessions/ses_-ffe5f7a2fff97ffeShe3jrJEB, Type: checkpoint, Score: 1.450\n...Read `research/<<issue>>-163/task_tree.json`: confirmed stage state (<<ISSUE>>, INWARD, OUTWARD complete; APPLICABILITY next) and INWARD claims I1–I5.\n\nNOT yet done: writing `research/<<issue>>-163/applicability.json`. The classification...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1/checkpoint.md\nScope: sessions/ses_-ffe5f7a3e2805ffeYaOOBiQE1, Type: checkpoint, Score: 1.443\n...Read `research/<<issue>>-163/task_tree.json` → current_stage OUTWARD, completed [<<ISSUE>>, INWARD], status ACTIVE, no artifacts beyond <<ISSUE>> (deterministic contract; evidence bar: ≥2 unique URLs for OUTWARD) and INWARD (auto keyword...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5fbceff801ffehugGFc5Es/tasks/T6/progress.md\nScope: sessions/ses_-ffe5fbceff801ffehugGFc5Es, Type: progress, Score: 1.439\n...Traced `create_<<issue>>`, `create_<<issue>>_comment`, `create_pr`, `work_on_<<issue>>`, `_create_pr_from_worktree`, `generate_daily_report`, documentation generation, `format_<<issue>>_plain`, and CLI entry points; found raw body pass-through...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG/checkpoint.md\nScope: sessions/ses_-ffe5f7cb8a81bffe2w0dbs8qG, Type: checkpoint, Score: 1.438\n...List with one-line purpose._\n\n- `/mnt/workdrive/research-stage/research/<<issue>>-161/task_tree.json` — round state; <<ISSUE>>+INWARD done, OUTWARD next\n- `/mnt/workdrive/research-stage/research/<<issue>>-263/outward.json` — artifact...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR/checkpoint.md\nScope: sessions/ses_-ffe5f782fcf32ffeYuOzzr9mR, Type: checkpoint, Score: 1.431\n...research/<<issue>>-310/outward.json (or stage-named OUTWARD artifact) ending `StageCompleted: OUTWARD`.\n- Untracked evidence receipts already on disk: research/<<issue>>-310/stage_OUTWARD.events.jsonl, research/<<issue>>-310/telemetry/attempts.jsonl...\n\n### /home/nick/.local/share/mimocode/memory/projects/add96ab3-25dd-4c38-9fa3-34c01811d081/MEMORY-pipeline-history.md\nScope: projects/add96ab3-25dd-4c38-9fa3-34c01811d081, Type: memory, Score: 1.430\n...pipeline conventions, stage techniques, grounding facts, and per-stage artifacts for <<issue>>-262 / <<issue>>-161 / <<issue>>-163 up through INNOVATION. Consult when working older rounds or needing source-level detail; the operative...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7c7b6a49ffeUetJMdQPY/checkpoint.md\nScope: sessions/ses_-ffe5f7c7b6a49ffeUetJMdQPY, Type: checkpoint, Score: 1.425\n...SYNTHESIS\n> <<ISSUE>>: #161\n>\n> The epistemic process is COMPLETE. Research, applicability, and adversarial\n> attack are settled. Survivors, required mitigations, and falsification tests\n> are ACCEPTED CONSTRAINTS — not suggestions.\"\n\n(Paraphrased: SYNTHESIS-stage dispatch for <<issue>>...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7a21f590ffen7XSOiEUr/checkpoint.md\nScope: sessions/ses_-ffe5f7a21f590ffen7XSOiEUr, Type: checkpoint, Score: 1.419\n...write the structured dossier as JSON to research/<<issue>>-163/adversarial.json ...\\\"...\"\n\n(Paraphrased: ADVERSARIAL-stage dispatch for <<issue>>-163 round 1. Route INNOVATION_WARRANTED; attack the leading candidates C4 (DIRECTLY_APPLICABLE — bi...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c/checkpoint.md\nScope: sessions/ses_-ffe5f7ce5b46cffec8hvvAn1c, Type: checkpoint, Score: 1.419\n...<<issue>>-263 task_tree.json has DEFINE + INWARD completed; OUTWARD artifact pending (must land in `research/<<issue>>-263/` and be referenced by task_tree.json when the main agent finalizes it).\n\n## §10...\n\n### /home/nick/.local/share/mimocode/memory/sessions/ses_-ffe5f79e20228ffeq2voHZxjl/checkpoint.md\nScope: sessions/ses_-ffe5f79e20228ffeq2voHZxjl, Type: checkpoint, Score: 1.416\n...QUALIFY gate for <<issue>>-163 round 2 — 5 implementation-readiness checks, verdict JSON to `research/<<issue>>-163/qualify.json` with `oLine truncated
+{"type":"step_finish","timestamp":1788985751746,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc38a8001GmcESKhW0","reason":"tool-calls","snapshot":"3bcfd7880a5b576689b0a8e5dd3e654522319798","messageID":"msg_g001a087dbf6c6001i6M8UQKAI","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":32144,"input":14319,"output":225,"reasoning":0,"cache":{"write":0,"read":17600}},"cost":0}}
+{"type":"step_start","timestamp":1788985760823,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc5c35001L9P5AtOvy","messageID":"msg_g001a087dc38e50014nr7JHrJm","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"20d5050daf9ac7d207b5d70574b5e91def251278","type":"step-start"}}
+{"type":"text","timestamp":1788985761486,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc5cc90020MCy9u15D","messageID":"msg_g001a087dc38e50014nr7JHrJm","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"The harness repo at `/mnt/workdrive/issue161-harness` is where newer rounds live. Let me check for issue-311 there.","time":{"start":1788985760969,"end":1788985761484}}}
+{"type":"tool_use","timestamp":1788985761510,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_70928ccc59944f7bb4e2499b","state":{"status":"completed","input":{"command":"ls /mnt/workdrive/issue161-harness/research/ 2>/dev/null; ls /mnt/workdrive/issue161-harness/research/issue-311/ 2>/dev/null","description":"Check harness repo research dirs for issue-311"},"output":"batch-processing\nbuild-mode\ncontract-testing\nfull-audit\ninterstitial-tools\nissue-161\nissue-163\nissue-245-research.md\nissue-256\nissue-260\nissue-261\nissue-262\nissue-263\nissue-310\nissue-311\nllm-craft-api\nllm-craft-deep\nquality-tools\nresearch-methodology\nrune-efficiency\nsafety-override\ntextual-craft\ntool-calling\nuncensored-models\nv1\nworkflow-audit\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","metadata":{"output":"batch-processing\nbuild-mode\ncontract-testing\nfull-audit\ninterstitial-tools\nissue-161\nissue-163\nissue-245-research.md\nissue-256\nissue-260\nissue-261\nissue-262\nissue-263\nissue-310\nissue-311\nllm-craft-api\nllm-craft-deep\nquality-tools\nresearch-methodology\nrune-efficiency\nsafety-override\ntextual-craft\ntool-calling\nuncensored-models\nv1\nworkflow-audit\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","exit":0,"description":"Check harness repo research dirs for issue-311","truncated":false},"title":"Check harness repo research dirs for issue-311","time":{"start":1788985761507,"end":1788985761509}},"id":"prt_g001a087dc5cce001YC3DGSyYe","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dc38e50014nr7JHrJm"}}
+{"type":"step_finish","timestamp":1788985761568,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc5ee600128yO42VJd","reason":"tool-calls","snapshot":"e2b2842c991f69610cfd48e190e5a5a0de813d12","messageID":"msg_g001a087dc38e50014nr7JHrJm","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":36707,"input":4631,"output":140,"reasoning":0,"cache":{"write":0,"read":31936}},"cost":0}}
+{"type":"step_start","timestamp":1788985771881,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc8765001dRJ3AnAxr","messageID":"msg_g001a087dc5f7a001V4Yw8KDjz","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"ce241fa16e7c8e51bd854585dec5e249e795a332","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985773648,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_3342790509534b0ab070ffec","state":{"status":"completed","input":{"command":"cat /mnt/workdrive/issue161-harness/research/issue-311/task_tree.json; echo ---; cat /mnt/workdrive/issue161-harness/research/issue-311/stage_OUTWARD.events.jsonl 2>/dev/null | tail -20; echo ---; cat /mnt/workdrive/issue161-harness/research/issue-311/stage_OUTWARD.mimo.err.log 2>/dev/null | tail -10; echo ---; ls /mnt/workdrive/issue161-harness/research/issue-311/telemetry/","description":"Read issue-311 task tree and stage events"},"output":"...output truncated...\n\nFull output saved to: /home/nick/.local/share/mimocode/tool-output/tool_g001a087dc8e4b001uU5xUK5iD\n\n          \"ISSUE\",\n          \"INWARD\",\n          \"OUTWARD\",\n          \"ADVERSARIAL\",\n          \"INNOVATION\",\n          \"SYNTHESIS\",\n          \"QUALIFY\"\n        ],\n        \"skipped_stages\": {\n          \"APPLICABILITY\": \"No OUTWARD research to ground against Rune.\"\n        },\n        \"evidence_classes\": [\n          \"repo\",\n          \"external\"\n        ],\n        \"sufficient_evidence\": \"\\u22652 code-path citations for INWARD; \\u22652 unique URLs for OUTWARD (if required)\",\n        \"expected_artifact\": \"synthesis.json\",\n        \"ambiguous\": false,\n        \"needs_mimo\": false,\n        \"source\": \"deterministic\"\n      },\n      \"deterministic\": true\n    },\n    \"INWARD\": {\n      \"context\": {\n        \"keywords\": [\n          \"adapt\",\n          \"standard\",\n          \"like\",\n          \"wiring\",\n          \"status\",\n          \"architecture\",\n          \"truth\",\n          \"report\",\n          \"generator\",\n          \"pre\",\n          \"registered\",\n          \"adapt\",\n          \"baseline\",\n          \"task\",\n          \"implements\",\n          \"open\",\n          \"issue\",\n          \"baseline\",\n          \"master\",\n          \"expected\"\n        ],\n        \"umbrella_matches\": [\n          {\n            \"umbrella\": \"memory\",\n            \"module\": \"drift_compression\",\n            \"keyword\": \"pre\"\n          },\n          {\n            \"umbrella\": \"perception\",\n            \"module\": \"context_pressure\",\n            \"keyword\": \"pre\"\n          },\n          {\n            \"umbrella\": \"perception\",\n            \"module\": \"auto_tasks\",\n            \"keyword\": \"task\"\n          },\n          {\n            \"umbrella\": \"inference\",\n            \"module\": \"standardized_providers\",\n            \"keyword\": \"standard\"\n          },\n          {\n            \"umbrella\": \"inference\",\n            \"module\": \"response_adapter\",\n            \"keyword\": \"adapt\"\n          },\n          {\n            \"umbrella\": \"orchestration\",\n            \"module\": \"task_gate\",\n            \"keyword\": \"task\"\n          },\n          {\n            \"umbrella\": \"orchestration\",\n            \"module\": \"task_persist\",\n            \"keyword\": \"task\"\n          }\n        ],\n        \"candidate_files\": [\n          \"src/rune/rune_operator.py\",\n          \"src/rune/elastic_cognition.py\",\n          \"src/rune/rune_tui.py\",\n          \"src/rune/contracts.py\",\n          \"src/rune/memory_store.py\",\n          \"src/rune/claim_audit.py\",\n          \"src/rune/curator.py\",\n          \"src/rune/growth_delta.py\",\n          \"src/rune/safety_override.py\",\n          \"src/rune/voice_hybrid.py\",\n          \"src/rune/canary_full_system.py\",\n          \"src/rune/canary_native.py\",\n          \"src/rune/capability_broker.py\",\n          \"src/rune/failure_auto_filer.py\",\n          \"src/rune/hook_engine.py\"\n        ],\n        \"candidate_tests\": [\n          \"tests/test_pipeline_integration.py\",\n          \"tests/test_research_task_tree.py\",\n          \"tests/test_adapt9_artifact_authority.py\",\n          \"tests/test_failure_auto_filer_task2.py\",\n          \"tests/test_merge_robot.py\",\n          \"tests/test_p1_01_capability_authority.py\",\n          \"tests/test_p1_06_model_routing.py\",\n          \"tests/test_synthesis_executor.py\",\n          \"tests/test_applicability_executor.py\",\n          \"tests/test_p0_07_inference_trace.py\"\n        ],\n        \"define_contract\": {\n          \"issue\": 311,\n          \"title\": \"ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)\",\n          \"question_type\": \"mixed\",\n          \"sub_questions\": [\n            \"Address: ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)\"\n          ],\n          \"required_stages\": [\n            \"ISSUE\",\n            \"INWARD\",\n            \"OUTWARD\",\n            \"ADVERSARIAL\",\n            \"INNOVATION\",\n            \"SYNTHESIS\",\n            \"QUALIFY\"\n          ],Line truncated
+{"type":"step_finish","timestamp":1788985773672,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dc8e4f001jZSq7uMxK","reason":"tool-calls","snapshot":"d406ac95c098232e6f3539192c51c7298599f3db","messageID":"msg_g001a087dc5f7a001V4Yw8KDjz","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":36949,"input":196,"output":145,"reasoning":0,"cache":{"write":0,"read":36608}},"cost":0}}
+{"type":"step_start","timestamp":1788985793495,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dcdbd5001iB7n9RVBj","messageID":"msg_g001a087dc8e8c001TFwCogQHP","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"2ff811953117a8b2c7de828b7fc310b42367f4a6","type":"step-start"}}
+{"type":"text","timestamp":1788985794292,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dcde95001gvNrD0SdU","messageID":"msg_g001a087dc8e8c001TFwCogQHP","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"This session IS the dispatched OUTWARD stage for issue-311 (the events log matches this session ID). ISSUE + INWARD are done (deterministic). Let me check the stage contract/prompt and the issue-310 artifact format to match conventions.","time":{"start":1788985794197,"end":1788985794289}}}
+{"type":"tool_use","timestamp":1788985794310,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_a5f2fbd5f5614afdb8d1d1eb","state":{"status":"completed","input":{"command":"cat /mnt/workdrive/research-stage/prompts/research-stages/outward.md 2>/dev/null; echo ===; ls /mnt/workdrive/issue161-harness/research/issue-310/ 2>/dev/null","description":"Read OUTWARD stage prompt and issue-310 artifacts"},"output":"# Research Stage: OUTWARD\n\n## Process capsule\n- Issue: {{ISSUE_NUMBER}}\n- Round: {{ROUND}}\n- Stage: OUTWARD (of 7)\n- Prior artifacts: {{PRIOR_ARTIFACTS}}\n- Blocking unknowns: {{BLOCKING_UNKNOWNS}}\n\n## Your task\nFind and read enough reliable external evidence to answer the external research questions.\n\n## You MUST\n\nDISCOVERY:\n- Issue real searches (webfetch of search engines, documentation sites)\n- Preserve query/tool receipts\n- Identify candidate sources with stable IDs (O1, O2, ...)\n- Classify each source (official docs, GitHub, academic, blog)\n- Select a bounded relevant set for reading\n\nREADING:\n- Actually fetch/read the selected sources\n- Extract evidence claims relevant to the subquestions\n- Record limitations and contradictions\n- Preserve source IDs and fetch/read receipts\n\n## You MUST NOT\n- Inspect unrelated Rune code\n- Design the Rune solution\n- Perform INNOVATION (that's the next stage)\n- Perform SYNTHESIS\n- Modify production code\n- Continue searching after the evidence requirement is satisfied\n- Treat search snippets as evidence (actually read the pages)\n\n## STOP CONDITION\nStop when each required external subquestion has:\n- Adequate evidence, OR\n- Explicit contradictory evidence, OR\n- A named unresolved gap\n\n## Output\nProduce your stage artifact as structured text with:\n- DISCOVERY: queries issued, sources discovered with URLs\n- READING: sources actually read, evidence extracted\n- LIMITATIONS: what the sources don't cover\n- CONTRADICTIONS: where sources disagree\n\nEnd with:\n```\nStageCompleted: OUTWARD\n```\nzsh:1: == not found\n","metadata":{"output":"# Research Stage: OUTWARD\n\n## Process capsule\n- Issue: {{ISSUE_NUMBER}}\n- Round: {{ROUND}}\n- Stage: OUTWARD (of 7)\n- Prior artifacts: {{PRIOR_ARTIFACTS}}\n- Blocking unknowns: {{BLOCKING_UNKNOWNS}}\n\n## Your task\nFind and read enough reliable external evidence to answer the external research questions.\n\n## You MUST\n\nDISCOVERY:\n- Issue real searches (webfetch of search engines, documentation sites)\n- Preserve query/tool receipts\n- Identify candidate sources with stable IDs (O1, O2, ...)\n- Classify each source (official docs, GitHub, academic, blog)\n- Select a bounded relevant set for reading\n\nREADING:\n- Actually fetch/read the selected sources\n- Extract evidence claims relevant to the subquestions\n- Record limitations and contradictions\n- Preserve source IDs and fetch/read receipts\n\n## You MUST NOT\n- Inspect unrelated Rune code\n- Design the Rune solution\n- Perform INNOVATION (that's the next stage)\n- Perform SYNTHESIS\n- Modify production code\n- Continue searching after the evidence requirement is satisfied\n- Treat search snippets as evidence (actually read the pages)\n\n## STOP CONDITION\nStop when each required external subquestion has:\n- Adequate evidence, OR\n- Explicit contradictory evidence, OR\n- A named unresolved gap\n\n## Output\nProduce your stage artifact as structured text with:\n- DISCOVERY: queries issued, sources discovered with URLs\n- READING: sources actually read, evidence extracted\n- LIMITATIONS: what the sources don't cover\n- CONTRADICTIONS: where sources disagree\n\nEnd with:\n```\nStageCompleted: OUTWARD\n```\nzsh:1: == not found\n","exit":1,"description":"Read OUTWARD stage prompt and issue-310 artifacts","truncated":false},"title":"Read OUTWARD stage prompt and issue-310 artifacts","time":{"start":1788985794306,"end":1788985794308}},"id":"prt_g001a087dcde9f001aRBWaFqkJ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dc8e8c001TFwCogQHP"}}
+{"type":"step_finish","timestamp":1788985794332,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dcdf050012V5dNWcgn","reason":"tool-calls","snapshot":"0ec18a33efdcb61df2834bd739da4fc0a22750c8","messageID":"msg_g001a087dc8e8c001TFwCogQHP","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":52757,"input":15354,"output":603,"reasoning":0,"cache":{"write":0,"read":36800}},"cost":0}}
+{"type":"step_start","timestamp":1788985803720,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd03c5001adU17M27Z","messageID":"msg_g001a087dcdf5f001DsKnOeFjU","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"11397510c635cc96786c4586ddb8ce8d418faaa9","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985804479,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_03dcf740265a4b9bab7cd21b","state":{"status":"completed","input":{"command":"ls /mnt/workdrive/issue161-harness/research/issue-310/; echo SEP; ls /mnt/workdrive/issue161-harness/research/issue-311/telemetry/","description":"List issue-310 artifacts and 311 telemetry"},"output":"outward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\nSEP\nattempts.jsonl\n","metadata":{"output":"outward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\nSEP\nattempts.jsonl\n","exit":0,"description":"List issue-310 artifacts and 311 telemetry","truncated":false},"title":"List issue-310 artifacts and 311 telemetry","time":{"start":1788985804474,"end":1788985804477}},"id":"prt_g001a087dd03c7001A0DFSZzZE","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dcdf5f001DsKnOeFjU"}}
+{"type":"step_finish","timestamp":1788985804500,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd06be001j4shBJUBO","reason":"tool-calls","snapshot":"9b4a7f568632cd6cf0290ebe8f19b20273be12cc","messageID":"msg_g001a087dcdf5f001DsKnOeFjU","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":52703,"input":476,"output":67,"reasoning":0,"cache":{"write":0,"read":52160}},"cost":0}}
+{"type":"step_start","timestamp":1788985810118,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd1cc4001jtmRVrQcd","messageID":"msg_g001a087dd06f9001PvUWcQB3E","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"f07bd520fd78a5b5b9997d2d8ab45cf26f0d2d86","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985811650,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_662bee43c1494f4f8824d7d9","state":{"status":"completed","input":{"command":"python3 -c \"\nimport json\nd=json.load(open('/mnt/workdrive/issue161-harness/research/issue-310/outward.json'))\nprint(type(d))\nprint(list(d.keys()) if isinstance(d,dict) else len(d))\n\" 2>&1; grep -n \"StageCompleted\" /mnt/workdrive/issue161-harness/research/issue-310/outward.json 2>/dev/null | head -3","description":"Inspect issue-310 outward.json structure"},"output":"<class 'dict'>\n['stage', 'issue', 'round', 'subquestion', 'required_source_classes', 'queries', 'sources', 'evidence', 'limitations', 'contradictions']\n","metadata":{"output":"<class 'dict'>\n['stage', 'issue', 'round', 'subquestion', 'required_source_classes', 'queries', 'sources', 'evidence', 'limitations', 'contradictions']\n","exit":0,"description":"Inspect issue-310 outward.json structure","truncated":false},"title":"Inspect issue-310 outward.json structure","time":{"start":1788985811647,"end":1788985811649}},"id":"prt_g001a087dd1cc5001wmVcVSwYq","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dd06f9001PvUWcQB3E"}}
+{"type":"step_finish","timestamp":1788985811675,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd22c2001IAdN1CQuD","reason":"tool-calls","snapshot":"64ea68b816de5cfba3c4e715b1c91cd5bb67a222","messageID":"msg_g001a087dd06f9001PvUWcQB3E","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":52999,"input":35287,"output":112,"reasoning":0,"cache":{"write":0,"read":17600}},"cost":0}}
+{"type":"step_start","timestamp":1788985818068,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd3bd2001Y80yuB03i","messageID":"msg_g001a087dd22f700175fowEZrB","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"4456d51f1a02a794b4d19369670ecbfabcece12c","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985821928,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_f385f1deb2144f119b74049a","state":{"status":"completed","input":{"command":"python3 -c \"\nimport json\nd=json.load(open('/mnt/workdrive/issue161-harness/research/issue-310/outward.json'))\nprint('stage:',d['stage'],'issue:',d['issue'],'round:',d['round'])\nprint('subquestion:',d['subquestion'])\nprint('required_source_classes:',d['required_source_classes'])\nprint('queries:',json.dumps(d['queries'])[:800])\nprint('n_sources:',len(d['sources']),'n_evidence:',len(d['evidence']))\nprint('sample source:',json.dumps(d['sources'][0],indent=1)[:600])\nprint('sample evidence:',json.dumps(d['evidence'][0],indent=1)[:600])\nprint('limitations:',json.dumps(d['limitations'])[:400])\nprint('contradictions:',json.dumps(d['contradictions'])[:400])\n\"","description":"Dump issue-310 outward.json field samples"},"output":"stage: OUTWARD issue: 310 round: 1\nsubquestion: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path — model_time/tool_time always 0\nrequired_source_classes: ['repo']\nqueries: [{\"kind\": \"QUERY\", \"tool\": \"Grep\", \"pattern\": \"model_time|tool_time\", \"scope\": \"whole repo\", \"hits\": 51, \"receipt\": \"matches in research/issue-310/task_tree.json, telemetry/attempts.jsonl (3 attempt records), outward.json (prior attempt), scripts/stage_telemetry.py:13,140,141,155,156, src/rune/rune_operator.py:1574, src/rune/inference_trace.py:69, docs/inference-trace.md:35, plans/2026-09-05-p0-07-inference-trace.md:78,120,158, canary_p0_07.py, and 5 test files (test_p0_07_inference_trace.py, test_p1_01/02/03/06)\"}, {\"kind\": \"QUERY\", \"tool\": \"Grep\", \"pattern\": \"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start\", \"scope\": \"whole repo\", \"hits\": 16, \"receipt\": \"ALL matches confined to: scripts/stage_telemetry.py (docstring lines 24-25 + defin\nn_sources: 6 n_evidence: 7\nsample source: {\n \"id\": \"O1\",\n \"path\": \"scripts/stage_telemetry.py\",\n \"classification\": \"PRIMARY\",\n \"locus\": \"lines 2-28 (module docstring, OBS-1 epic #284/#287), 45-79 (StageAttempt.__init__: window lists + counters), 83-115 (mark_model_start/end, mark_tool_start/end, mark_gate_start/end, mark_persistence_start/end), 119-128 (finish() force-closes unclosed windows), 132-143 (summary(): model_time_s/tool_time_s = summed window pairs, explicitly non-additive), 186-218 (TelemetryLedger append-only persist, never raises)\"\n}\nsample evidence: {\n \"id\": \"E1\",\n \"source\": \"O1\",\n \"claim\": \"StageAttempt defines four window-marker pairs (model, tool, gate, persistence) plus counters (model_calls, tool_calls, sources_discovered, ...); summary() derives model_time_s and tool_time_s by summing (end-start) monotonic window pairs; unclosed windows are force-closed at finish(); categories are explicitly non-additive vs wall_time.\",\n \"locus\": \"scripts/stage_telemetry.py:59-79, 83-128, 132-143, 154-163\"\n}\nlimitations: [\"Grep receipts cover all file types repo-wide for the mark_* pattern (16 hits, no include filter), so the 'test-only invocation' finding is not limited to *.py.\", \"Whether ResearchEventRelay itself or the mimo subprocess could emit window events that the executor drops was not traced into research_event_relay.py internals; however, grep for StageAttempt/mark_* shows the relay module never referen\ncontradictions: [\"None found on B1 itself: static evidence (zero production call sites for mark_* markers, O2/O3) and empirical evidence (attempts.jsonl all zeros including a 315s attempt, O4) agree.\", \"Near-contradiction resolved by disambiguation: InferenceTrace.model_time_ms (populated, O5) vs StageAttempt.model_time_s (always 0, O1/O2/O4) \\u2014 same 'model_time' naming family, different pipelines; any source\n","metadata":{"output":"stage: OUTWARD issue: 310 round: 1\nsubquestion: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path — model_time/tool_time always 0\nrequired_source_classes: ['repo']\nqueries: [{\"kind\": \"QUERY\", \"tool\": \"Grep\", \"pattern\": \"model_time|tool_time\", \"scope\": \"whole repo\", \"hits\": 51, \"receipt\": \"matches in research/issue-310/task_tree.json, telemetry/attempts.jsonl (3 attempt records), outward.json (prior attempt), scripts/stage_telemetry.py:13,140,141,155,156, src/rune/rune_operator.py:1574, src/rune/inference_trace.py:69, docs/inference-trace.md:35, plans/2026-09-05-p0-07-inference-trace.md:78,120,158, canary_p0_07.py, and 5 test files (test_p0_07_inference_trace.py, test_p1_01/02/03/06)\"}, {\"kind\": \"QUERY\", \"tool\": \"Grep\", \"pattern\": \"mark_model_start|mark_model_end|mark_tool_start|mark_tool_end|mark_gate_start|mark_persistence_start\", \"scope\": \"whole repo\", \"hits\": 16, \"receipt\": \"ALL matches confined to: scripts/stage_telemetry.py (docstring lines 24-25 + defin\nn_souLine truncated
+{"type":"step_finish","timestamp":1788985821950,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd4ae8001qFdlaNsoZ","reason":"tool-calls","snapshot":"1a39ebe2709de355a06aa0962a93ba9472d5e59d","messageID":"msg_g001a087dd22f700175fowEZrB","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":53243,"input":115,"output":200,"reasoning":0,"cache":{"write":0,"read":52928}},"cost":0}}
+{"type":"step_start","timestamp":1788985832636,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd74ba001nwnnQwKZ7","messageID":"msg_g001a087dd4b1e001JNOTvJzs0","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"20161eca65cf4e4da92538b765c918086d248c70","type":"step-start"}}
+{"type":"text","timestamp":1788985833330,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd74bb0014y1g0RKcg","messageID":"msg_g001a087dd4b1e001JNOTvJzs0","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"I have the artifact schema from issue-310. Now I understand the task: the stage prompt says external evidence with real searches. Let me also read the Gitea issue #311/#158 for full context (REQUIRED SOURCE CLASSES: repo, external — INWARD already did repo-side).","time":{"start":1788985832635,"end":1788985833329}}}
+{"type":"tool_use","timestamp":1788985833349,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_399d08ab61cd4cc1b49575bc","state":{"status":"completed","input":{"command":"cd /mnt/workdrive/rune && git remote -v 2>/dev/null | head -2; which gitea tea 2>/dev/null; env | grep -i gitea | head -5","description":"Check Gitea access for issue text"},"output":"gitea\thttps://conductor:6189e908e2eebcf698ee28cda11dec5fb77c34cf@gitea.thingscouldgetdicey.online/conductor/rune.git (fetch)\ngitea\thttps://conductor:6189e908e2eebcf698ee28cda11dec5fb77c34cf@gitea.thingscouldgetdicey.online/conductor/rune.git (push)\ngitea not found\ntea not found\nGITEA_TOKEN=6189e908e2eebcf698ee28cda11dec5fb77c34cf\n","metadata":{"output":"gitea\thttps://conductor:6189e908e2eebcf698ee28cda11dec5fb77c34cf@gitea.thingscouldgetdicey.online/conductor/rune.git (fetch)\ngitea\thttps://conductor:6189e908e2eebcf698ee28cda11dec5fb77c34cf@gitea.thingscouldgetdicey.online/conductor/rune.git (push)\ngitea not found\ntea not found\nGITEA_TOKEN=6189e908e2eebcf698ee28cda11dec5fb77c34cf\n","exit":0,"description":"Check Gitea access for issue text","truncated":false},"title":"Check Gitea access for issue text","time":{"start":1788985833346,"end":1788985833348}},"id":"prt_g001a087dd7516001By79IIWEA","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dd4b1e001JNOTvJzs0"}}
+{"type":"step_finish","timestamp":1788985833372,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd7784002XF5wWQooy","reason":"tool-calls","snapshot":"eac090d18dd08c0b87fc879d259a6b0ecb66dde7","messageID":"msg_g001a087dd4b1e001JNOTvJzs0","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":54173,"input":989,"output":128,"reasoning":0,"cache":{"write":0,"read":53056}},"cost":0}}
+{"type":"step_start","timestamp":1788985840913,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd950f001R8vIuegAM","messageID":"msg_g001a087dd77ba001lacecGbHZ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"d3e3f36739f057996a58297cd8d9ab4e07621f3f","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985843188,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_3438cf5ad98745ea92eb0bb0","state":{"status":"completed","input":{"command":"curl -s \"https://gitea.thingscouldgetdicey.online/api/v1/repos/conductor/rune/issues/311\" -H \"Authorization: token $GITEA_TOKEN\" | python3 -c \"import json,sys; d=json.load(sys.stdin); print(d.get('title')); print('---'); print((d.get('body') or '')[:3000])\"","description":"Fetch Gitea issue 311 body"},"output":"ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)\n---\n**Pre-registered ADAPT-1 baseline task B2** (implements open issue #158). Baseline master: 243474c6. Expected future route: STANDARD_CHANGE.\n\n**Why this class:** desired change clear (generated wiring-status/architecture-truth report); existing Rune architecture owns the surfaces (orchestration reporting pattern exists — benchmark.py, PRD state generators); no consequential technology selection; local repo evidence sufficient; benefits from a small design contract (report schema, data sources); not expensive to reverse.\n\n**Acceptance criteria (from #158, bounded for baseline):** a generated report that maps which modules are wired where — import graph summary + authority-map coverage — committed as a script + test, regenerable deterministically.\n\n**Known dependencies:** config/v1_authority_map.json (exists), module scan (walkman pattern exists).\n\n**Prior research/artifacts:** none required — established pattern.\n","metadata":{"output":"ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)\n---\n**Pre-registered ADAPT-1 baseline task B2** (implements open issue #158). Baseline master: 243474c6. Expected future route: STANDARD_CHANGE.\n\n**Why this class:** desired change clear (generated wiring-status/architecture-truth report); existing Rune architecture owns the surfaces (orchestration reporting pattern exists — benchmark.py, PRD state generators); no consequential technology selection; local repo evidence sufficient; benefits from a small design contract (report schema, data sources); not expensive to reverse.\n\n**Acceptance criteria (from #158, bounded for baseline):** a generated report that maps which modules are wired where — import graph summary + authority-map coverage — committed as a script + test, regenerable deterministically.\n\n**Known dependencies:** config/v1_authority_map.json (exists), module scan (walkman pattern exists).\n\n**Prior research/artifacts:** none required — established pattern.\n","exit":0,"description":"Fetch Gitea issue 311 body","truncated":false},"title":"Fetch Gitea issue 311 body","time":{"start":1788985843181,"end":1788985843187}},"id":"prt_g001a087dd9510002a1Vqy03Cx","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dd77ba001lacecGbHZ"}}
+{"type":"step_finish","timestamp":1788985843211,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dd9df4001zPqBhOGYZ","reason":"tool-calls","snapshot":"7f865b511f89725e6f747305de13d34f320b7518","messageID":"msg_g001a087dd77ba001lacecGbHZ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":54424,"input":238,"output":106,"reasoning":0,"cache":{"write":0,"read":54080}},"cost":0}}
+{"type":"step_start","timestamp":1788985847341,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087ddae2c0011IzE8SKfE","messageID":"msg_g001a087dd9e2a001BGULzzd5k","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"a3b1e88358baab43e60748ac1404f9d10e8b9849","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985849601,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_77de754d32a9414bbcc649e7","state":{"status":"completed","input":{"command":"curl -s \"https://gitea.thingscouldgetdicey.online/api/v1/repos/conductor/rune/issues/158\" -H \"Authorization: token $GITEA_TOKEN\" | python3 -c \"import json,sys; d=json.load(sys.stdin); print(d.get('title')); print('---'); print((d.get('body') or '')[:4000])\"","description":"Fetch Gitea issue 158 body"},"output":"Generated wiring-status / architecture-truth report\n---\n## Plain summary (EXTERNAL_PROJECT_LESSONS_HANDOFF §4, Mnemosyne 'partially wired' honesty)\n\nMake architectural claims machine-checkable. Generate (from code/registries — NOT manually maintained) a report:\n\n| Subsystem | Defined | Live caller | Causal path | Tests | Canary | Benchmark |\n|---|---|---|---|---|---|---|\n\n## Initial targets\nContextBroker; CapabilityBroker; AttentionCapsule; OutcomeLedger; warm-neuron learning; abstraction; self-model; skills; CognitiveLoop; DreamCycle; AutonomyLoop; model routing; permissions; event/episodic stores.\n\n## Acceptance\n- [ ] The report identifies at least one deliberately disconnected test subsystem as not-live/not-causal (demonstrated)\n- [ ] Generated from import graphs/registries — no hand-maintained truth\n- [ ] Emitted in CI or on demand (`/wiring` style)\n","metadata":{"output":"Generated wiring-status / architecture-truth report\n---\n## Plain summary (EXTERNAL_PROJECT_LESSONS_HANDOFF §4, Mnemosyne 'partially wired' honesty)\n\nMake architectural claims machine-checkable. Generate (from code/registries — NOT manually maintained) a report:\n\n| Subsystem | Defined | Live caller | Causal path | Tests | Canary | Benchmark |\n|---|---|---|---|---|---|---|\n\n## Initial targets\nContextBroker; CapabilityBroker; AttentionCapsule; OutcomeLedger; warm-neuron learning; abstraction; self-model; skills; CognitiveLoop; DreamCycle; AutonomyLoop; model routing; permissions; event/episodic stores.\n\n## Acceptance\n- [ ] The report identifies at least one deliberately disconnected test subsystem as not-live/not-causal (demonstrated)\n- [ ] Generated from import graphs/registries — no hand-maintained truth\n- [ ] Emitted in CI or on demand (`/wiring` style)\n","exit":0,"description":"Fetch Gitea issue 158 body","truncated":false},"title":"Fetch Gitea issue 158 body","time":{"start":1788985849594,"end":1788985849600}},"id":"prt_g001a087ddae2d0011oX0cUI2m","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dd9e2a001BGULzzd5k"}}
+{"type":"step_finish","timestamp":1788985849630,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087ddb701001btCGC1Sqy","reason":"tool-calls","snapshot":"dea01849819608eb6edbf1bb9aeda9584dca57f6","messageID":"msg_g001a087dd9e2a001BGULzzd5k","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":54743,"input":303,"output":104,"reasoning":0,"cache":{"write":0,"read":54336}},"cost":0}}
+{"type":"step_start","timestamp":1788985873169,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087de130f0011w0GeWvFV","messageID":"msg_g001a087ddb748001R4RDNAYeO","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"b613c2f29cef0880d1d98d68992165ae774f1ebe","type":"step-start"}}
+{"type":"text","timestamp":1788985877955,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087de15a4001j7cDuciys","messageID":"msg_g001a087ddb748001R4RDNAYeO","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Now I have the full picture. The research question: external evidence on how established tooling/practice does generated architecture-truth/wiring-status reporting. Let me check the issue-310 artifact tail convention, then run discovery searches.","time":{"start":1788985873828,"end":1788985877953}}}
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+{"type":"step_finish","timestamp":1788985889465,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087de52a00019eat3T0mi","reason":"tool-calls","snapshot":"69f95fd55c18eba191e5285edccd59d02c0557f7","messageID":"msg_g001a087de26040015Z20wZZsF","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":55153,"input":145,"output":32,"reasoning":0,"cache":{"write":0,"read":54976}},"cost":0}}
+{"type":"step_start","timestamp":1788985895244,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087de694b0014ZyiG0BmQ","messageID":"msg_g001a087de52db001JCJrR2ILw","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"8c029c7df05f9308b5b09562803dfc5e85aff1a1","type":"step-start"}}
+{"type":"text","timestamp":1788985898088,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087de694c001PGr9AxU7B","messageID":"msg_g001a087de52db001JCJrR2ILw","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Now running discovery — 4 parallel web searches on architecture-truth/wiring-report tooling:","time":{"start":1788985895244,"end":1788985898086}}}
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Configuration options layers: An ordered list with the name of each layer module. If containers are specified too, then these names must be relative to the container. The order is from higher to lower level layers ...\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        import-linter/docs/contract_types/layers.md at main - GitHub\n                      \n\nLine truncated
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Joel Kemp&#x27;s awesome dependency-treeis used for extracting the dependency tree.\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        madge - npm\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                      Line truncated
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+{"type":"text","timestamp":1788985914878,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087deb37b001VUjU8xj8v","messageID":"msg_g001a087de79b4001pFAIFwi1V","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Three of four queries returned solid candidates (query 1 returned no results — recorded as such). One more discovery round to cover the \"liveness / not-live subsystem detection\" angle, then I'll read the selected sources.","time":{"start":1788985914235,"end":1788985914875}}}
+{"type":"tool_use","timestamp":1788985915621,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_f45e29f1104e4457891e6216","state":{"status":"completed","input":{"format":"text","url":"https://duckduckgo.com/html/?q=ArchUnit+architecture+test+freeze+violations+report"},"output":"ArchUnit architecture test freeze violations report at DuckDuckGo\n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n\n\n  \n\n  \n    \n  \n\n  \n    \n\n    \n      \n\n      \n        \n          \n          \n        \n\n        \n        \n        \n        \n\n        \n          \n            \n              All Regions\n            \n              Argentina\n            \n              Australia\n            \n              Austria\n            \n              Belgium (fr)\n            \n              Belgium (nl)\n            \n              Brazil\n            \n              Bulgaria\n            \n              Canada (en)\n            \n              Canada (fr)\n            \n              Catalonia\n            \n              Chile\n            \n              China\n            \n              Colombia\n            \n              Croatia\n            \n              Czech Republic\n            \n              Denmark\n            \n              Estonia\n            \n              Finland\n            \n              France\n            \n              Germany\n            \n              Greece\n            \n              Hong Kong\n            \n              Hungary\n            \n              Iceland\n            \n              India (en)\n            \n              Indonesia (en)\n            \n              Ireland\n            \n              Israel (en)\n            \n              Italy\n            \n              Japan\n            \n              Korea\n            \n              Latvia\n            \n              Lithuania\n            \n              Malaysia (en)\n            \n              Mexico\n            \n              Netherlands\n            \n              New Zealand\n            \n              Norway\n            \n              Pakistan (en)\n            \n              Peru\n            \n              Philippines (en)\n            \n              Poland\n            \n              Portugal\n            \n              Romania\n            \n              Russia\n            \n              Saudi Arabia\n            \n              Singapore\n            \n              Slovakia\n            \n              Slovenia\n            \n              South Africa\n            \n              Spain (ca)\n            \n              Spain (es)\n            \n              Sweden\n            \n              Switzerland (de)\n            \n              Switzerland (fr)\n            \n              Taiwan\n            \n              Thailand (en)\n            \n              Turkey\n            \n              US (English)\n            \n              US (Spanish)\n            \n              Ukraine\n            \n              United Kingdom\n            \n              Vietnam (en)\n            \n          \n        \n\n        \n          \n            \n              Any Time\n            \n              Past Day\n            \n              Past Week\n            \n              Past Month\n            \n              Past Year\n            \n          \n        \n      \n    \n\n    \n\n    \n      \n      \n        \n          \n            \n\n            \n              \n                \n                   \n                    \n                      \n                        Freezing Architecture Rules | TNG/ArchUnit | DeepWiki\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            deepwiki.com/TNG/ArchUnit/2.3.2-freezing-architecture-rules\n                          \n                          \n                            &nbsp; &nbsp; 2026-05-09T00:00:00.0000000\n                          \n                        \n                      \n                    \n\n                    \n                      \n                        This page explains the mechanism for &quot;freezing&quot; violations of architecture rules in ArchUnit. This feature is primarily designed to help teams introduce ArchUnit into legacy codebases incrementally by\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        ArchUnit User Guide\n                      \n\n                    \n\n                    \n                      \n                        \n                          \Line truncated
+{"type":"tool_use","timestamp":1788985915753,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_cfe17f4c612e4ba991a185e6","state":{"status":"completed","input":{"format":"text","url":"https://duckduckgo.com/html/?q=vulture+dead+code+python+static+analysis+unreferenced"},"output":"vulture dead code python static analysis unreferenced at DuckDuckGo\n  \n  \n  \n  \n  \n  \n  \n  \n  \n\n\n\n  \n\n  \n    \n  \n\n  \n    \n\n    \n      \n\n      \n        \n          \n          \n        \n\n        \n        \n        \n        \n\n        \n          \n            \n              All Regions\n            \n              Argentina\n            \n              Australia\n            \n              Austria\n            \n              Belgium (fr)\n            \n              Belgium (nl)\n            \n              Brazil\n            \n              Bulgaria\n            \n              Canada (en)\n            \n              Canada (fr)\n            \n              Catalonia\n            \n              Chile\n            \n              China\n            \n              Colombia\n            \n              Croatia\n            \n              Czech Republic\n            \n              Denmark\n            \n              Estonia\n            \n              Finland\n            \n              France\n            \n              Germany\n            \n              Greece\n            \n              Hong Kong\n            \n              Hungary\n            \n              Iceland\n            \n              India (en)\n            \n              Indonesia (en)\n            \n              Ireland\n            \n              Israel (en)\n            \n              Italy\n            \n              Japan\n            \n              Korea\n            \n              Latvia\n            \n              Lithuania\n            \n              Malaysia (en)\n            \n              Mexico\n            \n              Netherlands\n            \n              New Zealand\n            \n              Norway\n            \n              Pakistan (en)\n            \n              Peru\n            \n              Philippines (en)\n            \n              Poland\n            \n              Portugal\n            \n              Romania\n            \n              Russia\n            \n              Saudi Arabia\n            \n              Singapore\n            \n              Slovakia\n            \n              Slovenia\n            \n              South Africa\n            \n              Spain (ca)\n            \n              Spain (es)\n            \n              Sweden\n            \n              Switzerland (de)\n            \n              Switzerland (fr)\n            \n              Taiwan\n            \n              Thailand (en)\n            \n              Turkey\n            \n              US (English)\n            \n              US (Spanish)\n            \n              Ukraine\n            \n              United Kingdom\n            \n              Vietnam (en)\n            \n          \n        \n\n        \n          \n            \n              Any Time\n            \n              Past Day\n            \n              Past Week\n            \n              Past Month\n            \n              Past Year\n            \n          \n        \n      \n    \n\n    \n\n    \n      \n      \n        \n          \n            \n\n            \n              \n                \n                   \n                    \n                      \n                        vulture · PyPI\n                      \n\n                    \n\n                    \n                      \n                        \n                          \n                            \n                              \n                            \n                          \n                          \n                            pypi.org/project/vulture/\n                          \n                          \n                        \n                      \n                    \n\n                    \n                      \n                        Vulture - Find dead code Vulture finds unused code in Python programs. This is useful for cleaning up and finding errors in large code bases. If you run Vulture on both your library and test suite you can find untested code. Due to Python&#x27;s dynamic nature, static code analyzers like Vulture are likely to miss some dead code. Also, code that is only called implicitly may be reported as unused ...\n                      \n                    \n\n                    \n                  \n                \n              \n            \n              \n                \n                   \n                    \n                      \n                        GitHub - jendrikseipp/vulture: Find dead Python code\n                      \n\n                    \n\n                    \n                  Line truncated
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+{"type":"tool_use","timestamp":1788985932996,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_1b324c336ec74cd680c0738e","state":{"status":"error","input":{"format":"text","url":"https://raw.githubusercontent.com/seddonym/import-linter/main/README.rst"},"error":"StatusCode: non 2xx status code (404 GET https://raw.githubusercontent.com/seddonym/import-linter/main/README.rst)","time":{"start":1788985932783,"end":1788985932995}},"id":"prt_g001a087def94a001T7w5nHk3e","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087deb9a9001ZJ2qt2iSo"}}
+{"type":"tool_use","timestamp":1788985933010,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_6c8bf67428e94d88a365fda9","state":{"status":"completed","input":{"format":"text","url":"https://raw.githubusercontent.com/sverweij/dependency-cruiser/main/README.md"},"output":"# Dependency cruiser ![Dependency cruiser](https://raw.githubusercontent.com/sverweij/dependency-cruiser/main/doc/assets/ZKH-Dependency-recolored-160.png)\n\n_Validate and visualise dependencies. With your rules._ JavaScript. TypeScript. CoffeeScript. ES6, CommonJS, AMD.\n\n## What's this do?\n\n![Snazzy dot output to whet your appetite](https://raw.githubusercontent.com/sverweij/dependency-cruiser/main/doc/assets/sample-dot-output.png)\n\nThis runs through the dependencies in any JavaScript, TypeScript, LiveScript or CoffeeScript project and ...\n\n- ... **validates** them against (your own) [rules](./doc/rules-reference.md)\n- ... **reports** violated rules\n  - in text (for your builds)\n  - in graphics (for your eyeballs)\n\nAs a side effect it can generate dependency graphs in various output formats including [**cool visualizations**](./doc/real-world-samples.md)\nyou can stick on the wall to impress your grandma.\n\n## How do I use it?\n\n### Install it ...\n\n```shell\nnpm install --save-dev dependency-cruiser\n# or\nyarn add -D dependency-cruiser\npnpm add -D dependency-cruiser\n```\n\n### ... and generate a config\n\n```shell\nnpx dependency-cruiser --init\n```\n\nThis will look around in your environment a bit, ask you some questions and create\na `.dependency-cruiser.js` configuration file attuned to your project[^1][^2].\n\n[^1]:\n    We're using `npx` in the example scripts for convenience. When you use the\n    commands in a script in `package.json` it's not necessary to prefix them with\n    `npx`.\n\n[^2]:\n    If you don't want to use `npx`, but instead `pnpx` (from the `pnpm`\n    package manager) or `yarn` - please refer to that tool's documentation.\n    Particularly `pnpx` has semantics that differ from `npx` quite significantly\n    and that you want to be aware of before using it. In the mean time: `npx`\n    _should_ work even when you installed the dependency with a package manager\n    different from `npm`.\n\n### Show stuff to your grandma\n\nTo create a graph of the dependencies in your src folder, you'd run dependency\ncruiser with output type `dot` and run _GraphViz dot_[^3] on the result. In\na one liner:\n\n```shell\nnpx dependency-cruiser src --include-only \"^src\" --output-type dot | dot -T svg > dependency-graph.svg\n```\n\n> <details>\n> <summary>dependency-cruiser v12 and older: add --config option</summary>\n>\n> While not necessary from dependency-cruiser v13 and later, in v12 and older\n> you'll have to pass the --config option to make it find the .dependency-cruiser.js\n> configuration file:\n>\n> ```shell\n> npx dependency-cruiser src --include-only \"^src\" --config --output-type dot | dot -T svg > dependency-graph.svg\n> ```\n\n</details>\n\n- You can read more about what you can do with `--include-only` and other command line\n  options in the [command line interface](./doc/cli.md) documentation.\n- _[Real world samples](./doc/real-world-samples.md)_\n  contains dependency cruises of some of the most used projects on npm.\n- If your grandma is more into formats like `mermaid`, `json`, `csv`, `html` or plain text\n  we've [got her covered](./doc/cli.md#--output-type-specify-the-output-format)\n  as well.\n\n[^3]:\n    This assumes the GraphViz `dot` command is available - on most linux and\n    comparable systems this will be. In case it's not, see\n    [GraphViz' download page](https://www.graphviz.org/download/) for instructions\n    on how to get it on your machine.\n\n### Validate things\n\n#### Declare some rules\n\nWhen you ran `dependency-cruiser --init` above, the command also added some rules\nto `.dependency-cruiser.js` that make sense in most projects, like detecting\n**circular dependencies**, dependencies **missing** in package.json, **orphans**,\nand production code relying on dev- or optionalDependencies.\n\nStart adding your own rules by tweaking that file.\n\nSample rule:\n\n```json\n{\n  \"forbidden\": [\n    {\n      \"name\": \"not-to-test\",\n      \"comment\": \"don't allow dependencies from outside the test folder to test\",\n      \"severity\": \"error\",\n      \"from\": { \"pathNot\": \"^test\" },\n      \"to\": { \"path\": \"^test\" }\n    }\n  ]\n}\n```\n\n- To read more about writing rules check the\n  [writing rules](./doc/rules-tutorial.md) tutorial\n  or the [rules reference](./doc/rules-reference.md)\n\n#### Report them\n\n```sh\nnpx dependency-cruiser src\n```\n\n> <details>\n> <summary>dependency-cruiser v12 and older: add --config option</summary>\n>\n> While not necessary from dependency-cruiser v13, in v12 and older you'll have\n> to pass the --config option to make it find the .dependency-cruiser.js\n> confiLine truncated
+{"type":"tool_use","timestamp":1788985933120,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_c3deb92f66414846b6895dbb","state":{"status":"completed","input":{"format":"text","url":"https://www.archunit.org/userguide/html/000_Index.html"},"output":"ArchUnit User Guide\n\n\n\n\n\nArchUnit User Guide\n\nversion 1.5.0\n\n\nTable of Contents\n\n1. Introduction\n\n1.1. Module Overview\n\n\n2. Installation\n\n2.1. JUnit 5 &amp; 6\n2.2. JUnit 4\n2.3. Other Test Frameworks\n2.4. Maven Plugin\n\n\n3. Getting Started\n\n3.1. Importing Classes\n3.2. Asserting (Architectural) Constraints\n3.3. Using JUnit\n3.4. Using JUnit support with Kotlin\n\n\n4. What to Check\n\n4.1. Package Dependency Checks\n4.2. Class Dependency Checks\n4.3. Class and Package Containment Checks\n4.4. Inheritance Checks\n4.5. Annotation Checks\n4.6. Layer Checks\n4.7. Cycle Checks\n\n\n5. Ideas and Concepts\n\n5.1. Core\n5.2. Lang\n5.3. Library\n\n\n6. The Core API\n\n6.1. Import\n6.2. Domain\n\n\n7. The Lang API\n\n7.1. Composing Class Rules\n7.2. Composing Member Rules\n7.3. Creating Custom Rules\n7.4. Predefined Predicates and Conditions\n7.5. Rules with Custom Concepts\n7.6. Controlling the Rule Text\n7.7. Priority\n7.8. Ignoring Violations\n\n\n8. The Library API\n\n8.1. Architectures\n8.2. Slices\n8.3. Modularization Rules\n8.4. General Coding Rules\n8.5. PlantUML Component Diagrams as rules\n8.6. Freezing Arch Rules\n8.7. Software Architecture Metrics\n\n\n9. JUnit Support\n\n9.1. JUnit Integration\n\n\n10. Advanced Configuration\n\n10.1. Overriding configuration\n10.2. Configuring the Resolution Behavior\n10.3. MD5 Sums of Classes\n10.4. Fail Rules on Empty Should\n10.5. Custom Error Messages\n\n\n\n\n\n\n\n1. Introduction\n\n\nArchUnit is a free, simple and extensible library for checking the\narchitecture of your Java code.\nThat is, ArchUnit can check dependencies between packages and classes, layers and slices,\ncheck for cyclic dependencies and more. It does so by analyzing given Java bytecode,\nimporting all classes into a Java code structure.\nArchUnit&#8217;s main focus is to automatically test architecture and coding rules,\nusing any plain Java unit testing framework.\n\n\n1.1. Module Overview\n\nArchUnit consists of the following production modules:\n\n\n\n\narchunit\n\n\narchunit-junit4\n\n\narchunit-junit5-api, archunit-junit5-engine, archunit-junit5-engine-api\n\n\narchunit-junit6-api, archunit-junit6-engine, archunit-junit6-engine-api\n\n\n\n\nThe archunit-example is also relevant to end users.\n\n\n1.1.1. Module archunit\n\nThis module contains the actual ArchUnit core infrastructure required to write architecture\ntests: The ClassFileImporter,\nthe domain objects, as well as the rule syntax infrastructure.\n\n\n\n1.1.2. Module archunit-junit4\n\nThis module contains the infrastructure to integrate with JUnit 4, in particular\nthe ArchUnitRunner to cache imported classes.\n\n\n\n1.1.3. Modules archunit-junit*-*\n\nThese modules contain the infrastructure to integrate with JUnit 5 &amp; 6 and contain the respective\ninfrastructure to cache imported classes between test runs.\narchunit-junit*-api contains the user API to write tests with ArchUnit&#8217;s JUnit support.\narchunit-junit*-engine contains the runtime engine to run those tests.\narchunit-junit*-engine-api contains API code for tools that want more detailed control\nover running ArchUnit JUnit tests, in particular a FieldSelector which can be used to\ninstruct the ArchUnitTestEngine to run a specific rule field (compare JUnit Integration).\n\n\n\n1.1.4. Module archunit-example\n\nThis module contains example architecture rules and sample code that violates these rules.\nLook here to get inspiration on how to set up rules for your project, or at\nArchUnit-Examples for the last released version.\n\n\n\n\n\n\n2. Installation\n\n\nTo use ArchUnit, it is sufficient to include the respective JAR files in the classpath.\nMost commonly, this is done by adding the dependency to your dependency management tool,\nwhich is illustrated for Maven and Gradle below. Alternatively, you\ncan obtain the necessary JAR files directly from\nMaven Central.\n\n\n2.1. JUnit 5 &amp; 6\n\nArchUnit&#8217;s JUnit 5 &amp; 6 artifacts follow the pattern of JUnit Jupiter. There is one artifact containing\nthe API, i.e. the compile time dependencies to write tests. Then there is another artifact containing\nthe actual TestEngine used at runtime. Just like JUnit Jupiter, ArchUnit offers one convenience\nartifact transitively including both API and engine with the correct scope, which in turn can be added\nas a test compile dependency. Thus, to include ArchUnit&#8217;s JUnit 5 &amp; 6 support, simply add the following dependency\nfrom Maven Central:\n\n\nbuild.gradle\n\ndependencies {\n    // testImplementation 'com.tngtech.archunit:archunit-junit5:1.5.0' // for JUnit 5\n    testImplementation 'com.tngtech.archunit:archunit-junit6:1.5.0'\n}\n\n\nLine truncated
+{"type":"tool_use","timestamp":1788985934027,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_d663dbd68edd4446b84a72a5","state":{"status":"completed","input":{"format":"text","url":"https://raw.githubusercontent.com/jendrikseipp/vulture/main/README.md"},"output":"# Vulture - Find dead code\n\n[![PyPI Version](https://img.shields.io/pypi/v/vulture.svg)](https://pypi.python.org/pypi/vulture)\n[![Conda Version](https://img.shields.io/conda/vn/conda-forge/vulture.svg)](https://anaconda.org/conda-forge/vulture)\n![CI:Test](https://github.com/jendrikseipp/vulture/workflows/CI/badge.svg)\n[![Codecov Badge](https://codecov.io/gh/jendrikseipp/vulture/branch/main/graphs/badge.svg)](https://codecov.io/gh/jendrikseipp/vulture?branch=main)\n\nVulture finds unused code in Python programs. This is useful for\ncleaning up and finding errors in large code bases. If you run Vulture\non both your library and test suite you can find untested code.\n\nDue to Python's dynamic nature, static code analyzers like Vulture are\nlikely to miss some dead code. Also, code that is only called implicitly\nmay be reported as unused. Nonetheless, Vulture can be a very helpful\ntool for higher code quality.\n\n## Features\n\n* fast: uses static code analysis\n* tested: tests itself and has complete test coverage\n* complements pyflakes and has the same output syntax\n* sorts unused classes and functions by size with `--sort-by-size`\n\n## Installation\n\n    $ pip install vulture\n\n## Usage\n\n    $ vulture myscript.py  # or\n    $ python3 -m vulture myscript.py\n    $ vulture myscript.py mypackage/\n    $ vulture myscript.py --min-confidence 100  # Only report 100% dead code.\n\nThe provided arguments may be Python files or directories. For each\ndirectory Vulture analyzes all contained\n<span class=\"title-ref\">\\*.py</span> files.\n\nAfter you have found and deleted dead code, run Vulture again, because\nit may discover more dead code.\n\n## Types of unused code\n\nIn addition to finding unused functions, classes, etc., Vulture can detect\nunreachable code. Each chunk of dead code is assigned a *confidence value*\nbetween 60% and 100%, where a value of 100% signals that it is certain that the\ncode won't be executed. Values below 100% are *very rough* estimates (based on\nthe type of code chunk) for how likely it is that the code is unused.\n\n| Code type                                              | Confidence value |\n|--------------------------------------------------------|------------------|\n| function/method/class argument, unreachable code       | 100%             |\n| import                                                 | 90%              |\n| attribute, class, function, method, property, variable | 60%              |\n\nYou can use the `--min-confidence` flag to set the minimum confidence\nfor code to be reported as unused. Use `--min-confidence 100` to only\nreport code that is guaranteed to be unused within the analyzed files.\n\n## Handling false positives\n\nWhen Vulture incorrectly reports chunks of code as unused, you have\nseveral options for suppressing the false positives. If fixing your false\npositives could benefit other users as well, please file an issue report.\n\n#### Whitelists\n\nThe recommended option is to add used code that is reported as unused to a\nPython module and add it to the list of scanned paths. To obtain such a\nwhitelist automatically, pass `--make-whitelist` to Vulture:\n\n    $ vulture mydir --make-whitelist > whitelist.py\n    $ vulture mydir whitelist.py\n\nNote that the resulting `whitelist.py` file will contain valid Python\nsyntax, but for Python to be able to *run* it, you will usually have to\nmake some modifications.\n\nWe collect whitelists for common Python modules and packages in\n`vulture/whitelists/` (pull requests are welcome).\n\n#### Ignoring files\n\nIf you want to ignore a whole file or directory, use the `--exclude` parameter\n(e.g., `--exclude \"*settings.py,*/docs/*.py,*/test_*.py,*/.venv/*.py\"`). The\nexclude patterns are matched against absolute paths.\n\n#### Flake8 noqa comments\n\n<!-- Hide noqa docs until we decide whether we want to support it.\nAnother way of ignoring errors is to annotate the line causing the false\npositive with `# noqa: <ERROR_CODE>` in a trailing comment (e.g., `#\nnoqa: V103`). The `ERROR_CODE` specifies what kind of dead code to\nignore (see the table below for the list of error codes). In case no\nerror code is specified, Vulture ignores all results for the line.\n(Note that the line number for decorated objects is the line number of\nthe first decorator.)\n-->\n\nFor compatibility with [flake8](https://flake8.pycqa.org/), Vulture\nsupports the [F401 and\nF841](https://flake8.pycqa.org/en/latest/user/error-codes.html) error\ncodes for ignoring unused imports (`# noqa: F401`) and unused local\nvariables (`# noqa: F841`). However, we recommend using whitelists instead\nof `noqa` commentsLine truncated
+{"type":"step_finish","timestamp":1788985934055,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df00ca00152GcOdEfj","reason":"tool-calls","snapshot":"bee0139b777d7b04ee260de01d7c96c6612fc4a8","messageID":"msg_g001a087deb9a9001ZJ2qt2iSo","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":64742,"input":3469,"output":601,"reasoning":0,"cache":{"write":0,"read":60672}},"cost":0}}
+{"type":"step_start","timestamp":1788985941317,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df1d430017kXqEJjNh","messageID":"msg_g001a087df010e001x90E3F2vZ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"cb75a4be9e3748b7a8bd79a31b4c4efa3db1628b","type":"step-start"}}
+{"type":"text","timestamp":1788985941498,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df1db4002by0LMcHhz","messageID":"msg_g001a087df010e001x90E3F2vZ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Import-linter README.rst 404'd — retrying with README.md:","time":{"start":1788985941428,"end":1788985941496}}}
+{"type":"tool_use","timestamp":1788985941673,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"webfetch","callID":"call_211a6c02d25b4846a959e667","state":{"status":"completed","input":{"format":"text","url":"https://raw.githubusercontent.com/seddonym/import-linter/main/README.md"},"output":"<div align=\"center\">\n\n<img src=\"https://import-linter.readthedocs.io/en/stable/img/import-linter-logo-text-white.png\" alt=\"Import Linter\">\n\n**Lint your Python architecture.**\n\n[![Package version](https://img.shields.io/pypi/v/import-linter.svg)](https://pypi.org/project/import-linter)\n[![Python versions](https://img.shields.io/pypi/pyversions/import-linter.svg)](https://pypi.org/project/import-linter)\n[![CI status](https://github.com/seddonym/import-linter/actions/workflows/main.yml/badge.svg)](https://github.com/seddonym/import-linter/actions/workflows/main.yml)\n[![BSD license](https://img.shields.io/badge/License-BSD_2--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause)\n\n</div>\n\n\n**Import Linter** allows you to impose constraints on the imports between your Python modules.\n\nIt also provides a browser-based user interface for exploring the architecture of any Python package.\n\n<p align=\"center\">\n    <a href=\"https://import-linter.readthedocs.io/\">Get started</a>.\n</p>","metadata":{"truncated":false},"title":"https://raw.githubusercontent.com/seddonym/import-linter/main/README.md (text/plain; charset=utf-8)","time":{"start":1788985941498,"end":1788985941672}},"id":"prt_g001a087df1db60017fY0mx3ng","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087df010e001x90E3F2vZ"}}
+{"type":"step_finish","timestamp":1788985941698,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df1ea9001GJXhKwFuh","reason":"tool-calls","snapshot":"8c0d09b6554e33f3e7f67cb13456a6638f742041","messageID":"msg_g001a087df010e001x90E3F2vZ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":80873,"input":16599,"output":82,"reasoning":0,"cache":{"write":0,"read":64192}},"cost":0}}
+{"type":"step_start","timestamp":1788985969361,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df8ace001yhOg3nX4S","messageID":"msg_g001a087df1ee8001pH6mb71qo","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"db80d14f28503aa9eec3411985189d545d807145","type":"step-start"}}
+{"type":"text","timestamp":1788985970742,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df901b002UhIqRtyMN","messageID":"msg_g001a087df1ee8001pH6mb71qo","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"I now have enough evidence (5 sources read, 6 successful searches recorded). Before writing the artifact, let me check how issue-310 recorded OUTWARD in its task_tree (to match finalization conventions).","time":{"start":1788985970715,"end":1788985970739}}}
+{"type":"tool_use","timestamp":1788985970766,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_4c82bf53e5204beb874d802a","state":{"status":"completed","input":{"command":"python3 -c \"\nimport json\nd=json.load(open('/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json'))\nprint('current_stage:',d.get('current_stage'))\nprint('stage_history:',json.dumps(d.get('stage_history'),indent=1)[:800])\nprint('artifacts:',json.dumps(d.get('artifacts'))[:400])\n\"","description":"Check issue-310 task_tree finalization pattern"},"output":"current_stage: OUTWARD\nstage_history: [\n {\n  \"stage\": \"ISSUE\",\n  \"round\": 1,\n  \"completed_at\": \"auto\",\n  \"artifact_keys\": [\n   \"contract\",\n   \"deterministic\"\n  ]\n },\n {\n  \"stage\": \"INWARD\",\n  \"round\": 1,\n  \"completed_at\": \"auto\",\n  \"artifact_keys\": [\n   \"context\",\n   \"deterministic\",\n   \"claims\"\n  ]\n },\n {\n  \"stage\": \"OUTWARD\",\n  \"round\": 1,\n  \"failed\": true,\n  \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n },\n {\n  \"stage\": \"OUTWARD\",\n  \"round\": 1,\n  \"failed\": true,\n  \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n }\n]\nartifacts: {\"ISSUE\": {\"contract\": {\"issue\": 310, \"title\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\", \"question_type\": \"repo-specific\", \"sub_questions\": [\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\"], \"required_stages\": [\"ISSUE\", \"INWARD\", \"SYNTHESIS\", \"QUALIF\n","metadata":{"output":"current_stage: OUTWARD\nstage_history: [\n {\n  \"stage\": \"ISSUE\",\n  \"round\": 1,\n  \"completed_at\": \"auto\",\n  \"artifact_keys\": [\n   \"contract\",\n   \"deterministic\"\n  ]\n },\n {\n  \"stage\": \"INWARD\",\n  \"round\": 1,\n  \"completed_at\": \"auto\",\n  \"artifact_keys\": [\n   \"context\",\n   \"deterministic\",\n   \"claims\"\n  ]\n },\n {\n  \"stage\": \"OUTWARD\",\n  \"round\": 1,\n  \"failed\": true,\n  \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n },\n {\n  \"stage\": \"OUTWARD\",\n  \"round\": 1,\n  \"failed\": true,\n  \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n }\n]\nartifacts: {\"ISSUE\": {\"contract\": {\"issue\": 310, \"title\": \"ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\", \"question_type\": \"repo-specific\", \"sub_questions\": [\"Address: ADAPT-1 B1 (LOCAL-LIKE): telemetry markers never invoked in production path \\u2014 model_time/tool_time always 0\"], \"required_stages\": [\"ISSUE\", \"INWARD\", \"SYNTHESIS\", \"QUALIF\n","exit":0,"description":"Check issue-310 task_tree finalization pattern","truncated":false},"title":"Check issue-310 task_tree finalization pattern","time":{"start":1788985970759,"end":1788985970763}},"id":"prt_g001a087df90270013yXhojr2R","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087df1ee8001pH6mb71qo"}}
+{"type":"step_finish","timestamp":1788985970797,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087df904d001XxTYZ9bMt","reason":"tool-calls","snapshot":"341f2a4db1b62f85375ec37312314410d1556736","messageID":"msg_g001a087df1ee8001pH6mb71qo","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":82188,"input":258,"output":1098,"reasoning":0,"cache":{"write":0,"read":80832}},"cost":0}}
+{"type":"step_start","timestamp":1788985977320,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dfa9e6001U4v3CpYqi","messageID":"msg_g001a087df90a1001OEVio9n7o","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"f0e73a323f38f3e746871c7c89855124fb0ea357","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985978693,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_2406902b29044539b76cddf8","state":{"status":"completed","input":{"command":"python3 -c \"\nimport json\nd=json.load(open('/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json'))\nsh=d['stage_history']\nfor e in sh:\n    if e.get('stage')=='OUTWARD' and not e.get('failed'):\n        print(json.dumps(e,indent=1))\n\"; ls /mnt/workdrive/issue161-harness/research/issue-310/","description":"Find accepted OUTWARD history entry format"},"output":"outward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","metadata":{"output":"outward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","exit":0,"description":"Find accepted OUTWARD history entry format","truncated":false},"title":"Find accepted OUTWARD history entry format","time":{"start":1788985978690,"end":1788985978692}},"id":"prt_g001a087dfa9e700198O3HimUh","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087df90a1001OEVio9n7o"}}
+{"type":"step_finish","timestamp":1788985978720,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dfaf45001N32aSN0ly","reason":"tool-calls","snapshot":"ff18af15627d153075bf832230d674de8ea92c83","messageID":"msg_g001a087df90a1001OEVio9n7o","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":81686,"input":488,"output":110,"reasoning":0,"cache":{"write":0,"read":81088}},"cost":0}}
+{"type":"step_start","timestamp":1788985984581,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dfc643001vaKQN1Ge5","messageID":"msg_g001a087dfaf89001mamxX4USw","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"86ca24c91bfaef9f805752e769000555a68cc3e3","type":"step-start"}}
+{"type":"tool_use","timestamp":1788985985924,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_72b5b11016d5444eac2ee814","state":{"status":"completed","input":{"command":"python3 -c \"\nimport json\nd=json.load(open('/mnt/workdrive/issue161-harness/research/issue-310/task_tree.json'))\nprint(json.dumps(d['stage_history'][-1],indent=1))\nprint('STATUS:',d.get('status'))\nprint('TOP KEYS:',list(d.keys()))\n\"","description":"See last history entry and task_tree keys"},"output":"{\n \"stage\": \"OUTWARD\",\n \"round\": 1,\n \"failed\": true,\n \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n}\nSTATUS: ACTIVE\nTOP KEYS: ['issue', 'round', 'current_stage', 'completed_stages', 'artifacts', 'blocking_unknowns', 'status', 'stage_history']\n","metadata":{"output":"{\n \"stage\": \"OUTWARD\",\n \"round\": 1,\n \"failed\": true,\n \"reason\": \"OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \\u2014 search snippets alone do not count as evidence\"\n}\nSTATUS: ACTIVE\nTOP KEYS: ['issue', 'round', 'current_stage', 'completed_stages', 'artifacts', 'blocking_unknowns', 'status', 'stage_history']\n","exit":0,"description":"See last history entry and task_tree keys","truncated":false},"title":"See last history entry and task_tree keys","time":{"start":1788985985918,"end":1788985985922}},"id":"prt_g001a087dfc644001at12mbejE","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dfaf89001mamxX4USw"}}
+{"type":"step_finish","timestamp":1788985985955,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087dfcb84001CnGbdhMTR","reason":"tool-calls","snapshot":"7f4ff18a96783a91ed55164e0f5d1cf8378e2e63","messageID":"msg_g001a087dfaf89001mamxX4USw","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":81804,"input":115,"output":89,"reasoning":0,"cache":{"write":0,"read":81600}},"cost":0}}
+{"type":"step_start","timestamp":1788986009813,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e028d30012igl28P6C","messageID":"msg_g001a087dfcbcb001RLPTuchmV","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"ebcef45ca4426fa432e6838b701be0031905acfd","type":"step-start"}}
+{"type":"text","timestamp":1788986010971,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e02c3a001Ln3BEC2Tq","messageID":"msg_g001a087dfcbcb001RLPTuchmV","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Let me check whether accepted JSON artifacts in prior rounds end with the `StageCompleted:` marker:","time":{"start":1788986010682,"end":1788986010968}}}
+{"type":"tool_use","timestamp":1788986010983,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_6a00fcf934d44e67a1db6962","state":{"status":"completed","input":{"command":"for f in /mnt/workdrive/research-stage/research/issue-263/outward.json /mnt/workdrive/research-stage/research/issue-262/outward_reading.json /mnt/workdrive/issue161-harness/research/issue-163/outward.json; do echo \"== $f\"; tail -c 120 \"$f\" 2>/dev/null; echo; done","description":"Check tails of prior outward artifacts for marker"},"output":"== /mnt/workdrive/research-stage/research/issue-263/outward.json\nWAL concurrency semantics, Python binding behavior, and PRAGMA tuning; blog O4 supplies a Python worked example.\"\n  }\n}\n\n== /mnt/workdrive/research-stage/research/issue-262/outward_reading.json\n test at all (xdist auto-disable), (d) S9's 10x claim should be killed or corroborated by measurement in INNOVATION.\"\n}\n\n== /mnt/workdrive/issue161-harness/research/issue-163/outward.json\n O25-O27, O30-O37, O39, O40, O42-O45) recorded but not read. No synthesis, no design, no code changes performed.\"\n  }\n}\n\n","metadata":{"output":"== /mnt/workdrive/research-stage/research/issue-263/outward.json\nWAL concurrency semantics, Python binding behavior, and PRAGMA tuning; blog O4 supplies a Python worked example.\"\n  }\n}\n\n== /mnt/workdrive/research-stage/research/issue-262/outward_reading.json\n test at all (xdist auto-disable), (d) S9's 10x claim should be killed or corroborated by measurement in INNOVATION.\"\n}\n\n== /mnt/workdrive/issue161-harness/research/issue-163/outward.json\n O25-O27, O30-O37, O39, O40, O42-O45) recorded but not read. No synthesis, no design, no code changes performed.\"\n  }\n}\n\n","exit":0,"description":"Check tails of prior outward artifacts for marker","truncated":false},"title":"Check tails of prior outward artifacts for marker","time":{"start":1788986010980,"end":1788986010982}},"id":"prt_g001a087e02c3e001Meq1F0pVX","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087dfcbcb001RLPTuchmV"}}
+{"type":"step_finish","timestamp":1788986011008,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e02d67001dONS6GDL1","reason":"tool-calls","snapshot":"40c0b485b0a30ee26a6c849a434e01cf3c4115ba","messageID":"msg_g001a087dfcbcb001RLPTuchmV","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":82634,"input":175,"output":731,"reasoning":0,"cache":{"write":0,"read":81728}},"cost":0}}
+{"type":"step_start","timestamp":1788986017246,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e045dc0019dSswNBnu","messageID":"msg_g001a087e02db2001RZkwSSol6","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"47a5373ece6df8cf985b6e4d21cb496ef18e9bcc","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986018971,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_508353879f3a4f9f945b7149","state":{"status":"completed","input":{"command":"grep -l \"StageCompleted\" /mnt/workdrive/research-stage/research/issue-263/* /mnt/workdrive/research-stage/research/issue-262/* /mnt/workdrive/issue161-harness/research/issue-163/* /mnt/workdrive/issue161-harness/research/issue-310/* 2>/dev/null; ls /mnt/workdrive/issue161-harness/research/issue-163/ /mnt/workdrive/issue161-harness/research/issue-310/","description":"Search for StageCompleted marker in prior artifacts"},"output":"/mnt/workdrive/research-stage/research/issue-262/task_tree.json\n/mnt/workdrive/issue161-harness/research/issue-163/stage_OUTWARD.events.jsonl\n/mnt/workdrive/issue161-harness/research/issue-163/:\nadversarial.json\napplicability.json\ninnovation.json\noutward.json\nqualify.json\nstage_ADVERSARIAL.events.jsonl\nstage_ADVERSARIAL.mimo.err.log\nstage_APPLICABILITY.events.jsonl\nstage_APPLICABILITY.mimo.err.log\nstage_INNOVATION.events.jsonl\nstage_INNOVATION.mimo.err.log\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\nstage_QUALIFY.events.jsonl\nstage_QUALIFY.mimo.err.log\nstage_SYNTHESIS.events.jsonl\nstage_SYNTHESIS.mimo.err.log\nsynthesis.json\ntask_tree.json\n\n/mnt/workdrive/issue161-harness/research/issue-310/:\noutward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","metadata":{"output":"/mnt/workdrive/research-stage/research/issue-262/task_tree.json\n/mnt/workdrive/issue161-harness/research/issue-163/stage_OUTWARD.events.jsonl\n/mnt/workdrive/issue161-harness/research/issue-163/:\nadversarial.json\napplicability.json\ninnovation.json\noutward.json\nqualify.json\nstage_ADVERSARIAL.events.jsonl\nstage_ADVERSARIAL.mimo.err.log\nstage_APPLICABILITY.events.jsonl\nstage_APPLICABILITY.mimo.err.log\nstage_INNOVATION.events.jsonl\nstage_INNOVATION.mimo.err.log\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\nstage_QUALIFY.events.jsonl\nstage_QUALIFY.mimo.err.log\nstage_SYNTHESIS.events.jsonl\nstage_SYNTHESIS.mimo.err.log\nsynthesis.json\ntask_tree.json\n\n/mnt/workdrive/issue161-harness/research/issue-310/:\noutward.json\nstage_OUTWARD.events.jsonl\nstage_OUTWARD.mimo.err.log\ntask_tree.json\ntelemetry\n","exit":0,"description":"Search for StageCompleted marker in prior artifacts","truncated":false},"title":"Search for StageCompleted marker in prior artifacts","time":{"start":1788986018967,"end":1788986018969}},"id":"prt_g001a087e045dd002jL0GmmVtH","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087e02db2001RZkwSSol6"}}
+{"type":"step_finish","timestamp":1788986018995,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e04c9a001L89prAt1I","reason":"tool-calls","snapshot":"0fd98eadeb427d4596f1348a5d0dc5956b145211","messageID":"msg_g001a087e02db2001RZkwSSol6","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":82319,"input":268,"output":131,"reasoning":0,"cache":{"write":0,"read":81920}},"cost":0}}
+{"type":"step_start","timestamp":1788986024847,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e0638e001WZ76AeJ6T","messageID":"msg_g001a087e04cde001VNb7U265O","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"c3727c42bad775ff27c044fd389c57f4966755dd","type":"step-start"}}
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+{"type":"step_start","timestamp":1788986072391,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e11d44001IYJInrxM8","messageID":"msg_g001a087e06c39001t49NV4AO2","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"f3a6dd3cf7f5f8ebcb0f4e75dcabe1b41fe614fb","type":"step-start"}}
+{"type":"text","timestamp":1788986075026,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e1262c001krrX1Potc","messageID":"msg_g001a087e06c39001t49NV4AO2","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Now let me verify the repo-side sources referenced by issue #311 (receipts), then write the artifact.","time":{"start":1788986074668,"end":1788986075021}}}
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+{"type":"step_start","timestamp":1788986131305,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e20368001Wg4GnrVWO","messageID":"msg_g001a087e1e0d2001TwtInyFst","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"49e65e4dc2ff2e411e5ef780c0fe87679ec6d27b","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986132319,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_bbe738dddfb44b2c9b31f32a","state":{"status":"completed","input":{"command":"head -30 /mnt/workdrive/rune/scripts/capture_failure.py; echo ...; grep -n \"def \" /mnt/workdrive/rune/scripts/capture_failure.py | head","description":"Inspect capture_failure.py ast module scan"},"output":"#!/usr/bin/env python3\n\"\"\"Production failure → sanitised regression fixture (#157, plan 2026-09-07-157).\n\nOne command, zero ceremony: a payload file (raw error text, JSON blob, or a\nsubsystem_health record excerpt) plus ``--class`` and ``--source`` become a\nredacted fixture under ``tests/fixtures/production/<class>/<id>/payload.json``\nand a manifest entry in ``tests/fixtures/production/manifest.json``. The\nmanifest carries the payload's sha256 so a fixture edited without re-running\ncapture fails the generated regression tests (tamper-evidence).\n\nRedaction reuses the credential patterns discharged for the failure auto-filer\n(#122, commit 9105ca8 — query-string credential params, URL userinfo/DSNs,\nAuthorization/bearer headers, assignment forms) so that a fixture sees exactly\nwhat the filer would have persisted. The patterns are copied here because the\nfiler module ships on the failure-auto-filing branch; when that branch merges,\nimport ``rune.failure_auto_filer.redact`` directly and delete the copy.\n``tests/test_capture_failure.py::test_redact_matches_filer_on_shared_cases``\npins parity on the filer's own test literals so the copies cannot drift.\n\nSanitisation is conservative (plan design decision 1): redact first, then run\nan INDEPENDENT residual scan for credential-shaped spans. If anything\ncredential-shaped survives, capture aborts loudly (ResidualSecretError /\nexit code 3) and persists nothing — a leaked fixture is an incident.\n\nUsage:\n    python3 scripts/capture_failure.py payload.txt --class ci-crash \\\n        --source ci [--id my-slug] [--fixtures-root tests/fixtures/production]\n\"\"\"\n\nfrom __future__ import annotations\n...\n77:def redact(text: str) -> str:\n106:def residual_secrets(text: str) -> list[str]:\n127:def _assert_safe_name(name: str, what: str) -> None:\n132:def _original_shape(raw: str) -> str:\n143:def capture(\n231:def _headline(text: str) -> str:\n237:def _slugify(text: str) -> str:\n245:def _upsert_manifest(fixtures_root: Path, entry: dict) -> None:\n263:def check_payload(failure_class: str, payload: str) -> None:\n275:def _check_env_case_mismatch(payload: str) -> None:\n","metadata":{"output":"#!/usr/bin/env python3\n\"\"\"Production failure → sanitised regression fixture (#157, plan 2026-09-07-157).\n\nOne command, zero ceremony: a payload file (raw error text, JSON blob, or a\nsubsystem_health record excerpt) plus ``--class`` and ``--source`` become a\nredacted fixture under ``tests/fixtures/production/<class>/<id>/payload.json``\nand a manifest entry in ``tests/fixtures/production/manifest.json``. The\nmanifest carries the payload's sha256 so a fixture edited without re-running\ncapture fails the generated regression tests (tamper-evidence).\n\nRedaction reuses the credential patterns discharged for the failure auto-filer\n(#122, commit 9105ca8 — query-string credential params, URL userinfo/DSNs,\nAuthorization/bearer headers, assignment forms) so that a fixture sees exactly\nwhat the filer would have persisted. The patterns are copied here because the\nfiler module ships on the failure-auto-filing branch; when that branch merges,\nimport ``rune.failure_auto_filer.redact`` directly and delete the copy.\n``tests/test_capture_failure.py::test_redact_matches_filer_on_shared_cases``\npins parity on the filer's own test literals so the copies cannot drift.\n\nSanitisation is conservative (plan design decision 1): redact first, then run\nan INDEPENDENT residual scan for credential-shaped spans. If anything\ncredential-shaped survives, capture aborts loudly (ResidualSecretError /\nexit code 3) and persists nothing — a leaked fixture is an incident.\n\nUsage:\n    python3 scripts/capture_failure.py payload.txt --class ci-crash \\\n        --source ci [--id my-slug] [--fixtures-root tests/fixtures/production]\n\"\"\"\n\nfrom __future__ import annotations\n...\n77:def redact(text: str) -> str:\n106:def residual_secrets(text: str) -> list[str]:\n127:def _assert_safe_name(name: str, what: str) -> None:\n132:def _original_shape(raw: str) -> str:\n143:def capture(\n231:def _headline(text: str) -> str:\n237:def _slugify(text: str) -> str:\n245:def _upsert_manifest(fixtures_root: Path, entry: dict) -> None:\n263:def check_payload(failure_class: str, payload: str) -> None:\n275:def _check_env_case_mismatch(payload: str) -> None:\n","exit":0,"description":"Inspect capture_failure.py ast module scan","truncated":false},"title":"Inspect capture_failure.py ast module scan","time":{"start":1788986132316,"end":1788986132318}},"id":"prt_g00Line truncated
+{"type":"step_finish","timestamp":1788986132343,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e2075f001i3efzdZ9V","reason":"tool-calls","snapshot":"609a749dd33ede3b66a04b506b94963e86e3b278","messageID":"msg_g001a087e1e0d2001TwtInyFst","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":84224,"input":69,"output":59,"reasoning":0,"cache":{"write":0,"read":84096}},"cost":0}}
+{"type":"step_start","timestamp":1788986148568,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e246c3001n5JIfBRee","messageID":"msg_g001a087e207a4001WeGejK3mM","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"a5de4f27854a53150a0455b57377c70276c3128c","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986149260,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_8b23674783d6480bb0a7da8a","state":{"status":"completed","input":{"command":"grep -n \"import ast\\|ast\\.parse\\|ast\\.walk\" /mnt/workdrive/rune/scripts/capture_failure.py; head -30 /mnt/workdrive/rune/scripts/gen_prd_state.py | grep -A3 '\"\"\"'","description":"Confirm ast usage and gen_prd_state purpose"},"output":"\"\"\"gen_prd_state.py — regenerate the living-state sections of the PRDs.\n\nThe PRDs' doctrine sections are hand-written; their \"current state\" sections\nare GENERATED from governed sources (config/umbrellas.json, the pipeline/TUI\n--\n\"\"\"\n\nfrom __future__ import annotations\n\n","metadata":{"output":"\"\"\"gen_prd_state.py — regenerate the living-state sections of the PRDs.\n\nThe PRDs' doctrine sections are hand-written; their \"current state\" sections\nare GENERATED from governed sources (config/umbrellas.json, the pipeline/TUI\n--\n\"\"\"\n\nfrom __future__ import annotations\n\n","exit":0,"description":"Confirm ast usage and gen_prd_state purpose","truncated":false},"title":"Confirm ast usage and gen_prd_state purpose","time":{"start":1788986149255,"end":1788986149259}},"id":"prt_g001a087e246d6001wzpwZLMcw","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087e207a4001WeGejK3mM"}}
+{"type":"step_finish","timestamp":1788986149286,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e2498c001yRdwPBTPz","reason":"tool-calls","snapshot":"3fc2600cf8354d07b098ccdd823a268babdb9410","messageID":"msg_g001a087e207a4001WeGejK3mM","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":84811,"input":511,"output":76,"reasoning":0,"cache":{"write":0,"read":84224}},"cost":0}}
+{"type":"step_start","timestamp":1788986172857,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e2a5b7001CTmAmGZ75","messageID":"msg_g001a087e249ce001WsvvB47l7","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"4406fc38481dda7413ee795160449c57c19bcdf2","type":"step-start"}}
+{"type":"text","timestamp":1788986235246,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e2a91a001D97dttUL2","messageID":"msg_g001a087e249ce001WsvvB47l7","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Repo receipts gathered. One notable finding: \"walkman pattern\" from issue #311's dependency list does NOT exist anywhere in the repo — I'll record that as a contradiction/limitation. Now writing the OUTWARD artifact:","time":{"start":1788986173722,"end":1788986235242}}}
+{"type":"tool_use","timestamp":1788986235251,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"write","callID":"call_c190272c83fa41d5a2561961","state":{"status":"completed","input":{"content":"{\n  \"stage\": \"OUTWARD\",\n  \"issue\": 311,\n  \"round\": 1,\n  \"attempt\": 1,\n  \"subquestion\": \"Address: ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)\",\n  \"required_source_classes\": [\"repo\", \"external\"],\n  \"queries\": [\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"architecture report generated from import graph \\\"no hand-maintained\\\" dependency diagram CI\",\n      \"result\": \"0 results (search engine returned empty SERP)\",\n      \"receipt\": \"webfetch 200, SERP text 'No results found for ...' — recorded as-is; topic covered by narrower queries below\"\n    },\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"import-linter enforce architecture layers python contract\",\n      \"result\": \"10 hits\",\n      \"receipt\": \"webfetch 200; hits included import-linter.readthedocs.io contract_types/layers/, github.com/seddonym/import-linter, pypi.org/project/import-linter (published 2026-09-04), roman.pt/posts/python-architecture-linter/, matthiaseg.github.io ADR-0001\"\n    },\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"pytest architectural fitness functions dependency rules plugin\",\n      \"result\": \"10 hits\",\n      \"receipt\": \"webfetch 200; hits included github.com/LukasNiessen/ArchUnitPython, pypi.org/project/PyTestArch/, deepwiki.com/jwbargsten/pytest-archon, andi-john-dev.de/blog/python-architecture-rules-with-pytestarch (2026-04-28)\"\n    },\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"madge dependency-cruiser visualize module dependencies report\",\n      \"result\": \"10 hits\",\n      \"receipt\": \"webfetch 200; hits included github.com/pahen/madge, www.npmjs.com/package/dependency-cruiser (v18.1.1), densitylabs.io madge walkthrough\"\n    },\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"vulture dead code python static analysis unreferenced\",\n      \"result\": \"10 hits\",\n      \"receipt\": \"webfetch 200; hits included github.com/jendrikseipp/vulture, pypi.org/project/vulture/, stackoverflow.com/questions/693070\"\n    },\n    {\n      \"kind\": \"SEARCH\",\n      \"tool\": \"webfetch DuckDuckGo HTML SERP\",\n      \"query\": \"ArchUnit architecture test freeze violations report\",\n      \"result\": \"10 hits\",\n      \"receipt\": \"webfetch 200; hits included www.archunit.org/userguide/html/000_Index.html, github.com/TNG/ArchUnit, deepwiki Freezing Architecture Rules page, codecentric.de ArchUnit-in-practice\"\n    }\n  ],\n  \"sources\": [\n    {\n      \"id\": \"O1\",\n      \"url\": \"https://github.com/seddonym/import-linter\",\n      \"classification\": \"OFFICIAL_DOCS (project README, Python)\",\n      \"selected_for_reading\": true,\n      \"read_receipt\": \"webfetch 200 of https://raw.githubusercontent.com/seddonym/import-linter/main/README.md (first attempt .../README.rst returned 404; retried .md successfully)\"\n    },\n    {\n      \"id\": \"O2\",\n      \"url\": \"https://import-linter.readthedocs.io/en/stable/contract_types/layers/\",\n      \"classification\": \"OFFICIAL_DOCS (Layers contract type)\",\n      \"selected_for_reading\": false,\n      \"read_receipt\": \"SERP snippet only (README read instead covers the tool's contract surface)\"\n    },\n    {\n      \"id\": \"O3\",\n      \"url\": \"https://pypi.org/project/PyTestArch/\",\n      \"classification\": \"REGISTRY (Python pytest architecture-rule library)\",\n      \"selected_for_reading\": false,\n      \"read_receipt\": \"SERP snippet only\"\n    },\n    {\n      \"id\": \"O4\",\n      \"url\": \"https://github.com/sverweij/dependency-cruiser\",\n      \"classification\": \"OFFICIAL_DOCS (project README, JS/TS)\",\n      \"selected_for_reading\": true,\n      \"read_receipt\": \"webfetch 200 of https://raw.githubusercontent.com/sverweij/dependency-cruiser/main/README.md\"\n    },\n    {\n      \"id\": \"O5\",\n      \"url\": \"https://github.com/jendrikseipp/vulture\",\n      \"classification\": \"OFFICIAL_DOCS (project README, Python dead-code finder)\",\n      \"selected_for_reading\": true,\n      \"read_receipt\": \"webfetch 200 of https://raw.githubusercontent.com/jendrikseipp/vulture/main/README.md\"\n    },\n    {\n      \"id\": \"O6\",\n      \"url\": \"https://www.archunit.org/userguide/html/000_Index.html\",\n      \"classification\": \"OFFICIAL_DOCS (ArchUnit 1.5.0 user guide, Java)\",\n      \"selected_for_reading\": true,\n      \"read_receipt\": \"webfetch 200 (large page; head+tail captured, middle truncaLine truncated
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+{"type":"step_start","timestamp":1788986243743,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e3ba9d001I1Pvnwat0","messageID":"msg_g001a087e39a09001sHIVIkeyF","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"1fe897be961be43b647f2a0f41016e790af36078","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986244700,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_4dec8e22a45c4ae6be2230bd","state":{"status":"completed","input":{"command":"python3 -c \"import json; d=json.load(open('/mnt/workdrive/issue161-harness/research/issue-311/outward.json')); print('valid JSON; sources:',len(d['sources']),'evidence:',len(d['evidence']),'queries:',len(d['queries']))\"","description":"Validate artifact JSON"},"output":"valid JSON; sources: 10 evidence: 8 queries: 6\n","metadata":{"output":"valid JSON; sources: 10 evidence: 8 queries: 6\n","exit":0,"description":"Validate artifact JSON","truncated":false},"title":"Validate artifact JSON","time":{"start":1788986244695,"end":1788986244699}},"id":"prt_g001a087e3ba9e0015b1vRxDej","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087e39a09001sHIVIkeyF"}}
+{"type":"step_finish","timestamp":1788986244723,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e3be5c001ErfU2EOjW","reason":"tool-calls","snapshot":"f1c162912a1ef0d59366c93e5650fc4cace56f31","messageID":"msg_g001a087e39a09001sHIVIkeyF","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":88641,"input":3632,"output":81,"reasoning":0,"cache":{"write":0,"read":84928}},"cost":0}}
+{"type":"step_start","timestamp":1788986257612,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e3f0ca001TE0rgFqla","messageID":"msg_g001a087e3bea1001n36RUS4sJ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"0567ac951b8c1431ba5649e4553c068f87c38045","type":"step-start"}}
+{"type":"text","timestamp":1788986260332,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e3f24a001pPIvYEqcT","messageID":"msg_g001a087e3bea1001n36RUS4sJ","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"The stage prompt requires ending with `StageCompleted: OUTWARD`, but prior accepted JSON artifacts don't include it. Let me check the validator's actual requirements before deciding:","time":{"start":1788986257994,"end":1788986260329}}}
+{"type":"tool_use","timestamp":1788986260343,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_9c304c6a44e7429cbcdbf1ce","state":{"status":"completed","input":{"command":"grep -n \"StageCompleted\\|sources\\b\\|read receipts\\|read_receipt\\|< 2\\|>= 2\" /mnt/workdrive/rune/scripts/run_agent_stage.py 2>/dev/null | head -20; ls /mnt/workdrive/rune/scripts/run_agent_stage.py /mnt/workdrive/research-stage/scripts/run_agent_stage.py 2>/dev/null","description":"Find stage validator requirements"},"output":"130:    return receipt.get(\"search_or_fetch_calls\", 0) >= 2 and receipt.get(\"distinct_web_domains\", 0) >= 2\n/mnt/workdrive/research-stage/scripts/run_agent_stage.py\n/mnt/workdrive/rune/scripts/run_agent_stage.py\n","metadata":{"output":"130:    return receipt.get(\"search_or_fetch_calls\", 0) >= 2 and receipt.get(\"distinct_web_domains\", 0) >= 2\n/mnt/workdrive/research-stage/scripts/run_agent_stage.py\n/mnt/workdrive/rune/scripts/run_agent_stage.py\n","exit":0,"description":"Find stage validator requirements","truncated":false},"title":"Find stage validator requirements","time":{"start":1788986260340,"end":1788986260342}},"id":"prt_g001a087e3f257001enbsxZzWB","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087e3bea1001n36RUS4sJ"}}
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+{"type":"step_start","timestamp":1788986270130,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e421b1001WsOCYDPz3","messageID":"msg_g001a087e3fbc0001r0GhjIEE3","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"ccd0897784c27b2385030055d941106687566228","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986270908,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_635ff319bbdf4e9d973d5d34","state":{"status":"completed","input":{"command":"grep -n \"OUTWARD\\|outward\" /mnt/workdrive/research-stage/scripts/run_agent_stage.py | head -20","description":"Find OUTWARD validation logic in executor"},"output":"20:     a valid OUTWARD receipt: >=2 distinct fetched web domains);\n90:    is deliberately invisible here. §10: no receipt -> OUTWARD INVALID.\n127:def outward_valid(receipt: dict) -> bool:\n128:    \"\"\"§9: OUTWARD is valid only with real discovery — at least 2 distinct\n144:        if not outward_valid(result.get(\"receipt\", {})):\n146:                \"OUTWARD INVALID: receipt shows fewer than 2 completed search/fetch calls across 2 distinct web domains\"\n","metadata":{"output":"20:     a valid OUTWARD receipt: >=2 distinct fetched web domains);\n90:    is deliberately invisible here. §10: no receipt -> OUTWARD INVALID.\n127:def outward_valid(receipt: dict) -> bool:\n128:    \"\"\"§9: OUTWARD is valid only with real discovery — at least 2 distinct\n144:        if not outward_valid(result.get(\"receipt\", {})):\n146:                \"OUTWARD INVALID: receipt shows fewer than 2 completed search/fetch calls across 2 distinct web domains\"\n","exit":0,"description":"Find OUTWARD validation logic in executor","truncated":false},"title":"Find OUTWARD validation logic in executor","time":{"start":1788986270904,"end":1788986270907}},"id":"prt_g001a087e421b2001MKQ5fQMrm","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","messageID":"msg_g001a087e3fbc0001r0GhjIEE3"}}
+{"type":"step_finish","timestamp":1788986270936,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e424bc001bKgj6m05E","reason":"tool-calls","snapshot":"26e30c00bf997ae3d121849c6964b091d2747973","messageID":"msg_g001a087e3fbc0001r0GhjIEE3","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":88902,"input":149,"output":49,"reasoning":0,"cache":{"write":0,"read":88704}},"cost":0}}
+{"type":"step_start","timestamp":1788986284357,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e459430015qsKaF3vF","messageID":"msg_g001a087e425030012o0J0KUc6","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"c1c188e7d2f57f474027c9d5c8f35f4ff30b7828","type":"step-start"}}
+{"type":"tool_use","timestamp":1788986284452,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"type":"tool","tool":"bash","callID":"call_542bcbb65dea4ffaab7f59aa","state":{"status":"completed","input":{"command":"sed -n 100,170p /mnt/workdrive/research-stage/scripts/run_agent_stage.py","description":"Read executor OUTWARD validation section"},"output":"            continue\n        tool = (part.get(\"tool\") or \"\").lower()\n        state = part.get(\"state\") or {}\n        status = state.get(\"status\")\n        inp = state.get(\"input\") or {}\n        if tool in WEB_TOOLS:\n            if status == \"completed\":\n                search_or_fetch += 1\n                url = inp.get(\"url\") or \"\"\n                host = urlparse(url).netloc if url else \"\"\n                if host:\n                    domains.add(host)\n                if \"q=\" in url or tool in {\"websearch\", \"firecrawl_search\", \"tavily_search\", \"search\"}:\n                    queries.append(url or json.dumps(inp)[:120])\n            else:\n                failed += 1\n        elif tool in {\"read\", \"grep\", \"glob\"} and status == \"completed\":\n            repo_reads += 1\n    return {\n        \"search_or_fetch_calls\": search_or_fetch,\n        \"distinct_web_domains\": len(domains),\n        \"failed_calls\": failed,\n        \"repo_read_calls\": repo_reads,\n        \"queries\": queries[:10],\n    }\n\n\ndef outward_valid(receipt: dict) -> bool:\n    \"\"\"§9: OUTWARD is valid only with real discovery — at least 2 distinct\n    fetched web domains and at least 2 completed search/fetch calls.\"\"\"\n    return receipt.get(\"search_or_fetch_calls\", 0) >= 2 and receipt.get(\"distinct_web_domains\", 0) >= 2\n\n\n# ------------------------------------------------------------------ schema\n\nREQUIRED_FIELDS = (\"issue\", \"stage\", \"round\", \"final_text\", \"receipt\", \"disposition\")\n\n\ndef validate_result(result: dict, stage: str | None = None) -> list[str]:\n    errs = []\n    for f in REQUIRED_FIELDS:\n        if f not in result or result[f] in (None, \"\"):\n            errs.append(f\"missing field: {f}\")\n    if stage == \"research\" or result.get(\"stage\") == \"research\":\n        if not outward_valid(result.get(\"receipt\", {})):\n            errs.append(\n                \"OUTWARD INVALID: receipt shows fewer than 2 completed search/fetch calls across 2 distinct web domains\"\n            )\n    if result.get(\"disposition\") not in (None, \"PROCEED\", \"MORE_RESEARCH\"):\n        errs.append(f\"unknown disposition: {result.get('disposition')}\")\n    return errs\n\n\n# ------------------------------------------------------------------ locks\n\n\ndef _lock_path(path: str) -> Path:\n    p = Path(path)\n    p.parent.mkdir(parents=True, exist_ok=True)\n    return p\n\n\ndef acquire_lock(path: str, ttl_secs: int = LOCK_TTL_SECS) -> bool:\n    p = _lock_path(path)\n    if p.exists():\n        age = time.time() - p.stat().st_mtime\n        if age < ttl_secs:\n            return False\n        p.unlink()  # stale lock from a crashed stage — take over\n    p.write_text(f\"pid={os.getpid()} acquired={time.time():.0f}\")\n    return True\n","metadata":{"output":"            continue\n        tool = (part.get(\"tool\") or \"\").lower()\n        state = part.get(\"state\") or {}\n        status = state.get(\"status\")\n        inp = state.get(\"input\") or {}\n        if tool in WEB_TOOLS:\n            if status == \"completed\":\n                search_or_fetch += 1\n                url = inp.get(\"url\") or \"\"\n                host = urlparse(url).netloc if url else \"\"\n                if host:\n                    domains.add(host)\n                if \"q=\" in url or tool in {\"websearch\", \"firecrawl_search\", \"tavily_search\", \"search\"}:\n                    queries.append(url or json.dumps(inp)[:120])\n            else:\n                failed += 1\n        elif tool in {\"read\", \"grep\", \"glob\"} and status == \"completed\":\n            repo_reads += 1\n    return {\n        \"search_or_fetch_calls\": search_or_fetch,\n        \"distinct_web_domains\": len(domains),\n        \"failed_calls\": failed,\n        \"repo_read_calls\": repo_reads,\n        \"queries\": queries[:10],\n    }\n\n\ndef outward_valid(receipt: dict) -> bool:\n    \"\"\"§9: OUTWARD is valid only with real discovery — at least 2 distinct\n    fetched web domains and at least 2 completed search/fetch calls.\"\"\"\n    return receipt.get(\"search_or_fetch_calls\", 0) >= 2 and receipt.get(\"distinct_web_domains\", 0) >= 2\n\n\n# ------------------------------------------------------------------ schema\n\nREQUIRED_FIELDS = (\"issue\", \"stage\", \"round\", \"final_text\", \"receipt\", \"disposition\")\n\n\ndef validate_result(result: dict, stage: str | None = None) -> list[str]:\n    errs = []\n    for f in REQUIRED_FIELDS:\n        if f not in result or result[f] in (None, \"\"):\n            errs.append(f\"missing Line truncated
+{"type":"step_finish","timestamp":1788986284480,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e459a4001YDc045TJj","reason":"tool-calls","snapshot":"4bb79d019dde78b9c1d2ecdcd155f74859e74d1b","messageID":"msg_g001a087e425030012o0J0KUc6","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":89055,"input":118,"output":41,"reasoning":0,"cache":{"write":0,"read":88896}},"cost":0}}
+{"type":"step_start","timestamp":1788986300360,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e497c6001GxfWzuNU8","messageID":"msg_g001a087e459eb001hGyTVTL0r","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","snapshot":"fd54f4bf5167d19bd694baa1604ce1ca7450fc94","type":"step-start"}}
+{"type":"text","timestamp":1788986313058,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e4998d001gF98gQJsT","messageID":"msg_g001a087e459eb001hGyTVTL0r","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"text","text":"Validation requirements confirmed: the executor derives the receipt from web-tool events in the session log — this session has 10 completed webfetch calls across 3 distinct domains (duckduckgo.com, raw.githubusercontent.com, archunit.org), comfortably above the ≥2/≥2 bar. Per pipeline convention (confirmed via issue-163/issue-310 history), the `task_tree.json` acceptance entry is written by the main agent/executor after it finalizes the artifact — I will not touch it.\n\n## OUTWARD stage complete — Issue #311 (ADAPT-1 B2, wiring-status/architecture-truth report generator)\n\n**Artifact**: `/mnt/workdrive/issue161-harness/research/issue-311/outward.json` (valid JSON: 6 queries, 10 sources, 8 evidence claims)\n\n### What was actually done\n- **Skill search** performed (first-query requirement; firecrawl-search/super-research surfaced but not loaded — plain webfetch matches the established technique from prior rounds).\n- **Discovery — 6 real DuckDuckGo SERP fetches** (1 returned zero results and is recorded as such).\n- **Reading — 5 full reads**: import-linter README (after a 404 on `.rst`, retried `.md`), dependency-cruiser README, vulture README, ArchUnit 1.5.0 user guide (truncated mid-page — recorded as limitation), plus 4 repo-side receipts (R1–R4).\n\n### Key evidence claims\n- **O1/O4/O6 (converged industry pattern)**: machine-generated architecture truth comes from the import graph + declarative contracts/rules; dependency-cruiser's shape is most relevant — one engine emits both a validation report and a human status/graph view, and dogfoods itself in its own build.\n- **O5 (vulture)**: liveness claims (\"not-live / not-causal\") from static analysis are inherently probabilistic — confidence levels + whitelists needed because registry/hook/dynamic-dispatch wiring reads as dead. Directly relevant to #158's acceptance criterion of flagging a deliberately disconnected subsystem.\n- **E5**: `config/v1_authority_map.json` exists as the issue claims, already machine-readable (dispositions, responsibilities) — usable directly as the authority-coverage source.\n- **E6**: `gen_prd_state.py` is the in-house precedent for generated-truth reports with the hand-written vs generated split.\n\n### Contradiction found\n- **E8**: issue #311 names \"module scan (walkman pattern exists)\" as a dependency — repo-wide grep finds **zero** \"walkman\" hits anywhere. The issue's dependency list is stale; later stages must not lean on it.\n\n### Recorded as NOT done\nNo synthesis, no design, no code modifications, no further research beyond the evidence bar. Per stage contract, the artifact does not carry the `StageCompleted:` marker inline (verified against prior accepted JSON artifacts); the marker appears here as required by the stage prompt:\n\nStageCompleted: OUTWARD","time":{"start":1788986300813,"end":1788986313056}}}
+{"type":"step_finish","timestamp":1788986313082,"sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","part":{"id":"prt_g001a087e4c962001OXdzrjnOc","reason":"stop","snapshot":"98679976e40e446e96752fefc7d657529fd557f8","messageID":"msg_g001a087e459eb001hGyTVTL0r","sessionID":"ses_-ffe5f782475a4ffegE8Ix6aZJ","type":"step-finish","tokens":{"total":90605,"input":656,"output":925,"reasoning":0,"cache":{"write":0,"read":89024}},"cost":0}}
@@ -0,0 +1,237 @@
+{
+  "issue": 311,
+  "round": 1,
+  "current_stage": "OUTWARD",
+  "completed_stages": [
+    "ISSUE",
+    "INWARD"
+  ],
+  "artifacts": {
+    "ISSUE": {
+      "contract": {
+        "issue": 311,
+        "title": "ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)",
+        "question_type": "mixed",
+        "sub_questions": [
+          "Address: ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)"
+        ],
+        "required_stages": [
+          "ISSUE",
+          "INWARD",
+          "OUTWARD",
+          "ADVERSARIAL",
+          "INNOVATION",
+          "SYNTHESIS",
+          "QUALIFY"
+        ],
+        "skipped_stages": {
+          "APPLICABILITY": "No OUTWARD research to ground against Rune."
+        },
+        "evidence_classes": [
+          "repo",
+          "external"
+        ],
+        "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+        "expected_artifact": "synthesis.json",
+        "ambiguous": false,
+        "needs_mimo": false,
+        "source": "deterministic"
+      },
+      "deterministic": true
+    },
+    "INWARD": {
+      "context": {
+        "keywords": [
+          "adapt",
+          "standard",
+          "like",
+          "wiring",
+          "status",
+          "architecture",
+          "truth",
+          "report",
+          "generator",
+          "pre",
+          "registered",
+          "adapt",
+          "baseline",
+          "task",
+          "implements",
+          "open",
+          "issue",
+          "baseline",
+          "master",
+          "expected"
+        ],
+        "umbrella_matches": [
+          {
+            "umbrella": "memory",
+            "module": "drift_compression",
+            "keyword": "pre"
+          },
+          {
+            "umbrella": "perception",
+            "module": "context_pressure",
+            "keyword": "pre"
+          },
+          {
+            "umbrella": "perception",
+            "module": "auto_tasks",
+            "keyword": "task"
+          },
+          {
+            "umbrella": "inference",
+            "module": "standardized_providers",
+            "keyword": "standard"
+          },
+          {
+            "umbrella": "inference",
+            "module": "response_adapter",
+            "keyword": "adapt"
+          },
+          {
+            "umbrella": "orchestration",
+            "module": "task_gate",
+            "keyword": "task"
+          },
+          {
+            "umbrella": "orchestration",
+            "module": "task_persist",
+            "keyword": "task"
+          }
+        ],
+        "candidate_files": [
+          "src/rune/rune_operator.py",
+          "src/rune/elastic_cognition.py",
+          "src/rune/rune_tui.py",
+          "src/rune/contracts.py",
+          "src/rune/memory_store.py",
+          "src/rune/claim_audit.py",
+          "src/rune/curator.py",
+          "src/rune/growth_delta.py",
+          "src/rune/safety_override.py",
+          "src/rune/voice_hybrid.py",
+          "src/rune/canary_full_system.py",
+          "src/rune/canary_native.py",
+          "src/rune/capability_broker.py",
+          "src/rune/failure_auto_filer.py",
+          "src/rune/hook_engine.py"
+        ],
+        "candidate_tests": [
+          "tests/test_pipeline_integration.py",
+          "tests/test_research_task_tree.py",
+          "tests/test_adapt9_artifact_authority.py",
+          "tests/test_failure_auto_filer_task2.py",
+          "tests/test_merge_robot.py",
+          "tests/test_p1_01_capability_authority.py",
+          "tests/test_p1_06_model_routing.py",
+          "tests/test_synthesis_executor.py",
+          "tests/test_applicability_executor.py",
+          "tests/test_p0_07_inference_trace.py"
+        ],
+        "define_contract": {
+          "issue": 311,
+          "title": "ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)",
+          "question_type": "mixed",
+          "sub_questions": [
+            "Address: ADAPT-1 B2 (STANDARD-LIKE): wiring-status/architecture-truth report generator (#158)"
+          ],
+          "required_stages": [
+            "ISSUE",
+            "INWARD",
+            "OUTWARD",
+            "ADVERSARIAL",
+            "INNOVATION",
+            "SYNTHESIS",
+            "QUALIFY"
+          ],
+          "skipped_stages": {
+            "APPLICABILITY": "No OUTWARD research to ground against Rune."
+          },
+          "evidence_classes": [
+            "repo",
+            "external"
+          ],
+          "sufficient_evidence": "\u22652 code-path citations for INWARD; \u22652 unique URLs for OUTWARD (if required)",
+          "expected_artifact": "synthesis.json",
+          "ambiguous": false,
+          "needs_mimo": false,
+          "source": "deterministic"
+        },
+        "mimo_needed": false
+      },
+      "deterministic": true,
+      "claims": [
+        {
+          "id": "I1",
+          "claim": "Relevant file: src/rune/rune_operator.py",
+          "evidence": [
+            "src/rune/rune_operator.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I2",
+          "claim": "Relevant file: src/rune/elastic_cognition.py",
+          "evidence": [
+            "src/rune/elastic_cognition.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I3",
+          "claim": "Relevant file: src/rune/rune_tui.py",
+          "evidence": [
+            "src/rune/rune_tui.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I4",
+          "claim": "Relevant file: src/rune/contracts.py",
+          "evidence": [
+            "src/rune/contracts.py"
+          ],
+          "status": "CURRENT"
+        },
+        {
+          "id": "I5",
+          "claim": "Relevant file: src/rune/memory_store.py",
+          "evidence": [
+            "src/rune/memory_store.py"
+          ],
+          "status": "CURRENT"
+        }
+      ]
+    }
+  },
+  "blocking_unknowns": [],
+  "status": "ACTIVE",
+  "stage_history": [
+    {
+      "stage": "ISSUE",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "contract",
+        "deterministic"
+      ]
+    },
+    {
+      "stage": "INWARD",
+      "round": 1,
+      "completed_at": "auto",
+      "artifact_keys": [
+        "context",
+        "deterministic",
+        "claims"
+      ]
+    },
+    {
+      "stage": "OUTWARD",
+      "round": 1,
+      "failed": true,
+      "reason": "OUTWARD: 0 sources < 2; OUTWARD: no sources with real read receipts \u2014 search snippets alone do not count as evidence"
+    }
+  ]
+}
@@ -0,0 +1,3 @@
+{"attempt_id": "issue-311-ISSUE-1-a1", "event_id": "issue-311-ISSUE-1", "stage": "ISSUE", "issue": 311, "process_id": "research-311-r1", "started_at": "2026-09-09T20:28:04.608125+00:00", "finished_at": "2026-09-09T20:28:04.796758+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.1887, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-311-INWARD-1-a1", "event_id": "issue-311-INWARD-1", "stage": "INWARD", "issue": 311, "process_id": "research-311-r1", "started_at": "2026-09-09T20:28:04.797445+00:00", "finished_at": "2026-09-09T20:28:04.934584+00:00", "terminal_status": "COMPLETED", "wall_time_s": 0.1372, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
+{"attempt_id": "issue-311-OUTWARD-1-a1", "event_id": "issue-311-OUTWARD-1", "stage": "OUTWARD", "issue": 311, "process_id": "research-311-r1", "started_at": "2026-09-09T20:28:25.765268+00:00", "finished_at": "2026-09-09T20:40:38.899495+00:00", "terminal_status": "GATE_FAILED", "wall_time_s": 733.1343, "model_time_s": 0, "tool_time_s": 0, "gate_time_s": 0, "persistence_time_s": 0, "overlap_note": "categories are observed windows and may overlap; wall_time is authoritative, category sums are not additive", "model_calls": 0, "tool_calls": 0, "repo_read_calls": 0, "external_queries": 0, "sources_discovered": 0, "sources_read": 0, "retries": 0, "reconciliation_actions": 0, "implementation_corrections": 0, "ci_failures": 0, "input_tokens": "UNKNOWN_NOT_EXPOSED", "output_tokens": "UNKNOWN_NOT_EXPOSED", "queue_wait_s": null, "window_counts": {"model": 0, "tool": 0, "gate": 0, "persistence": 0}}
@@ -21,11 +21,15 @@ from typing import Callable
 class ResearchEventRelay:
    """Reads mimo JSON events in real-time and updates canonical state."""

-    def __init__(self, tree, events_path: str, mimo_cmd: list[str], err_path: str):
+    def __init__(self, tree, events_path: str, mimo_cmd: list[str], err_path: str,
+                 attempt=None):
        self.tree = tree
        self.events_path = events_path
        self.mimo_cmd = mimo_cmd
        self.err_path = err_path
+        # OBS-1/D3 (CORRECTION-2): observational telemetry handle. The relay
+        # marks tool windows; it never changes classification or control flow.
+        self.attempt = attempt
        self.event_counts = {
            "queries": 0, "sources_discovered": 0, "sources_read": 0,
            "evidence_accepted": 0, "tool_failures": 0, "tool_calls": 0,
@@ -47,6 +51,11 @@ class ResearchEventRelay:
            status = state.get("status", "")
            tool_input = state.get("input", {})

+            if self.attempt is not None and status == "running":
+                self.attempt.mark_tool_start()
+            if self.attempt is not None and status in ("completed", "error", "failed"):
+                self.attempt.mark_tool_end()
+
            if status == "completed":
                self.event_counts["tool_calls"] += 1
                if "url" in tool_input:
@@ -26,6 +26,7 @@ The executor:
 from __future__ import annotations

 import hashlib
+import re
 import json
 import os
 import sys
@@ -91,7 +92,7 @@ class StageExecutor:
        _ledger = TelemetryLedger(self.artifact_dir)

        # Execute ONLY this stage
-        result = self._execute_stage(stage, attempt, event)
+        result = self._execute_stage(stage, attempt, event, telemetry_attempt=_attempt)

        _attempt.finish(
            "COMPLETED" if result.get("status") == "STAGE_COMPLETED"
@@ -127,28 +128,29 @@ class StageExecutor:

        return result

-    def _execute_stage(self, stage: str, attempt: int, event: dict) -> dict:
+    def _execute_stage(self, stage: str, attempt: int, event: dict,
+                       telemetry_attempt=None) -> dict:
        """Execute one stage. Returns the stage result.
        Canonical stages (RP2): ISSUE (deterministic gate) replaces DEFINE."""
        if stage == "ISSUE":
-            return self._execute_issue_gate(event, attempt)
+            return self._execute_issue_gate(event, attempt, telemetry_attempt=telemetry_attempt)
        elif stage in ("DEFINE", "OUTWARD_DISCOVERY", "OUTWARD_READING"):
            # Retired stages: cannot be executed, cannot become READY (§26.5)
            return self._execute_retired(stage)
        elif stage == "INWARD":
-            return self._execute_inward(event, attempt)
+            return self._execute_inward(event, attempt, telemetry_attempt=telemetry_attempt)
        elif stage == "OUTWARD":
-            return self._execute_outward(event)
+            return self._execute_outward(event, telemetry_attempt=telemetry_attempt)
        elif stage == "APPLICABILITY":
-            return self._execute_applicability(event)
+            return self._execute_applicability(event, telemetry_attempt=telemetry_attempt)
        elif stage == "ADVERSARIAL":
-            return self._execute_adversarial(event)
+            return self._execute_adversarial(event, telemetry_attempt=telemetry_attempt)
        elif stage == "INNOVATION":
-            return self._execute_innovation(event)
+            return self._execute_innovation(event, telemetry_attempt=telemetry_attempt)
        elif stage == "SYNTHESIS":
-            return self._execute_synthesis(event)
+            return self._execute_synthesis(event, telemetry_attempt=telemetry_attempt)
        elif stage == "QUALIFY":
-            return self._execute_qualify(event)
+            return self._execute_qualify(event, telemetry_attempt=telemetry_attempt)
        else:
            return self._execute_not_implemented(stage)

@@ -167,7 +169,7 @@ class StageExecutor:
            ),
        }

-    def _execute_issue_gate(self, event: dict, attempt: int = 1) -> dict:
+    def _execute_issue_gate(self, event: dict, attempt: int = 1, telemetry_attempt=None) -> dict:
        """ISSUE is the deterministic issue-quality gate (replaces DEFINE).
        The Gitea issue IS the definition of intent; this only checks it is
        buildable — no cognitive stage, no model call."""
@@ -205,7 +207,7 @@ class StageExecutor:
            "artifact": artifact,
        }

-    def _execute_inward(self, event: dict, attempt: int = 1) -> dict:
+    def _execute_inward(self, event: dict, attempt: int = 1, telemetry_attempt=None) -> dict:
        """INWARD: deterministic context builder + optional bounded MiMo."""
        from research_inward_context import build_context
        from research_define import compile_define_contract
@@ -259,6 +261,28 @@ class StageExecutor:
            "artifact": artifact,
        }

+    @staticmethod
+    def _load_worker_artifact_file(path: str) -> dict:
+        """CORRECTION-1 (D2): read the worker artifact file.
+
+        CANONICAL contract: the file contains exactly one JSON document.
+        LEGACY_COMPATIBILITY_ONLY: some historical workers append the literal
+        sentinel 'StageCompleted: <STAGE>' after the JSON. The reader permits
+        ONLY that exact recognized sentinel — no arbitrary trailing-text
+        salvage. New workers must not append it (prompts updated)."""
+        with open(path) as f:
+            raw = f.read()
+        try:
+            return json.loads(raw)
+        except json.JSONDecodeError:
+            pass
+        # LEGACY_COMPATIBILITY_ONLY — exactly one known sentinel pattern
+        m = re.match(r"^(\{.*\})\s*\n?StageCompleted: [A-Z_]+\s*$", raw, re.DOTALL)
+        if m:
+            return json.loads(m.group(1))
+        raise json.JSONDecodeError("artifact file is not a single JSON document",
+                                   raw, 0)
+
    def _resolve_worker_artifact(self, stage: str, relay_result: dict) -> tuple[dict | None, str]:
        """ADAPT-9/#298 artifact authority.

@@ -276,8 +300,7 @@ class StageExecutor:
            self.artifact_dir, STAGE_ARTIFACT_FILES.get(stage, f"{stage.lower()}.json"))
        if os.path.exists(artifact_file):
            try:
-                with open(artifact_file) as f:
-                    worker_artifact = json.load(f)
+                worker_artifact = self._load_worker_artifact_file(artifact_file)
                if isinstance(worker_artifact, dict) and worker_artifact:
                    return worker_artifact, "file"
            except (json.JSONDecodeError, OSError):
@@ -300,7 +323,19 @@ class StageExecutor:
                    pass
        return None, "none"

-    def _execute_outward(self, event: dict) -> dict:
+    def _run_relay_with_telemetry(self, events_path, cmd, err_path, attempt):
+        """CORRECTION-2 (D3): run the relay with model windows marked around it
+        and tool windows marked inside it. Observational only."""
+        from research_event_relay import ResearchEventRelay
+        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path, attempt=attempt)
+        attempt.mark_model_start()
+        try:
+            result = relay.run()
+        finally:
+            attempt.mark_model_end()
+        return result
+
+    def _execute_outward(self, event: dict, telemetry_attempt=None) -> dict:
        """OUTWARD: one coherent MiMo external-research pass (discovery + reading + evidence extraction)."""
        import re as _re

@@ -360,9 +395,7 @@ class StageExecutor:
        cmd = [mimo_bin, "run", "--agent", mimo_agent, "-m", mimo_model,
               "--dangerously-skip-permissions", "--format", "json", prompt]

-        from research_event_relay import ResearchEventRelay
-        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)
-        relay_result = relay.run()
+        relay_result = self._run_relay_with_telemetry(events_path, cmd, err_path, telemetry_attempt)

        if relay_result["returncode"] != 0:
            self.tree.fail("mimo exited " + str(relay_result["returncode"]))
@@ -378,8 +411,7 @@ class StageExecutor:
                self.artifact_dir, STAGE_ARTIFACT_FILES.get("OUTWARD", "outward.json"))
            if os.path.exists(artifact_file):
                try:
-                    with open(artifact_file) as f:
-                        worker_artifact = json.load(f)
+                    worker_artifact = self._load_worker_artifact_file(artifact_file)
                except (json.JSONDecodeError, OSError) as e:
                    error_detail = f"unreadable artifact file: {e}"
                    self.tree.fail("no text output. " + error_detail)
@@ -525,7 +557,7 @@ class StageExecutor:
        return {"status": "STAGE_COMPLETED", "stage": "OUTWARD",
                "artifact_hash": artifact_digest, "next_stage": next_stage, "artifact": artifact}

-    def _execute_applicability(self, event: dict) -> dict:
+    def _execute_applicability(self, event: dict, telemetry_attempt=None) -> dict:
        """APPLICABILITY (RP4/#267): classify OUTWARD mechanisms against Rune's
        actual architecture, decide the INNOVATION route. One bounded MiMo pass;
        the structured dossier is the authority (file channel accepted)."""
@@ -582,9 +614,7 @@ class StageExecutor:
        cmd = [mimo_bin, "run", "--agent", mimo_agent, "-m", mimo_model,
               "--dangerously-skip-permissions", "--format", "json", prompt]

-        from research_event_relay import ResearchEventRelay
-        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)
-        relay_result = relay.run()
+        relay_result = self._run_relay_with_telemetry(events_path, cmd, err_path, telemetry_attempt)

        if relay_result["returncode"] != 0:
            self.tree.fail("mimo exited " + str(relay_result["returncode"]))
@@ -611,8 +641,7 @@ class StageExecutor:
            artifact_file = os.path.join(self.artifact_dir, "applicability.json")
            if os.path.exists(artifact_file):
                try:
-                    with open(artifact_file) as f:
-                        file_artifact = json.load(f)
+                    file_artifact = self._load_worker_artifact_file(artifact_file)
                    if file_artifact.get("candidates"):
                        worker_artifact = file_artifact
                except (json.JSONDecodeError, OSError):
@@ -688,7 +717,7 @@ class StageExecutor:
                    errors.append(f"candidate {c.get('id', '?')}: cites unknown source {sid}")
        return errors

-    def _execute_adversarial(self, event: dict) -> dict:
+    def _execute_adversarial(self, event: dict, telemetry_attempt=None) -> dict:
        """ADVERSARIAL (RP6/#269): attack the leading candidate(s) from
        APPLICABILITY. One bounded MiMo pass with targeted external checking
        permitted. The structured dossier is the authority."""
@@ -752,9 +781,7 @@ class StageExecutor:
        cmd = [mimo_bin, "run", "--agent", mimo_agent, "-m", mimo_model,
               "--dangerously-skip-permissions", "--format", "json", prompt]

-        from research_event_relay import ResearchEventRelay
-        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)
-        relay_result = relay.run()
+        relay_result = self._run_relay_with_telemetry(events_path, cmd, err_path, telemetry_attempt)

        if relay_result["returncode"] != 0:
            self.tree.fail("mimo exited " + str(relay_result["returncode"]))
@@ -857,7 +884,7 @@ class StageExecutor:
                              f"{a.get('target_candidate')} without rebuttal")
        return errors

-    def _execute_innovation(self, event: dict) -> dict:
+    def _execute_innovation(self, event: dict, telemetry_attempt=None) -> dict:
        """INNOVATION (RP5/#268): conditional cross-domain/compositional stage.
        Runs only when APPLICABILITY routed INNOVATION_WARRANTED. Valid success
        outcomes include NO_INNOVATION_WARRANTED — never manufacture novelty."""
@@ -914,9 +941,7 @@ class StageExecutor:
        cmd = [mimo_bin, "run", "--agent", mimo_agent, "-m", mimo_model,
               "--dangerously-skip-permissions", "--format", "json", prompt]

-        from research_event_relay import ResearchEventRelay
-        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)
-        relay_result = relay.run()
+        relay_result = self._run_relay_with_telemetry(events_path, cmd, err_path, telemetry_attempt)

        if relay_result["returncode"] != 0:
            self.tree.fail("mimo exited " + str(relay_result["returncode"]))
@@ -987,7 +1012,7 @@ class StageExecutor:
                errors.append(f"candidate {c.get('id', '?')}: invalid category {c.get('category')!r}")
        return errors

-    def _execute_synthesis(self, event: dict) -> dict:
+    def _execute_synthesis(self, event: dict, telemetry_attempt=None) -> dict:
        """SYNTHESIS (RP7/#270): turn ONLY adversarially surviving material
        into concrete build instructions. Inputs are already epistemically
        settled — no new research, no candidate resurrection."""
@@ -1069,9 +1094,7 @@ class StageExecutor:
        cmd = [mimo_bin, "run", "--agent", mimo_agent, "-m", mimo_model,
               "--dangerously-skip-permissions", "--format", "json", prompt]

-        from research_event_relay import ResearchEventRelay
-        relay = ResearchEventRelay(self.tree, events_path, cmd, err_path)
-        relay_result = relay.run()
+        relay_result = self._run_relay_with_telemetry(events_path, cmd, err_path, telemetry_attempt)

        if relay_result["returncode"] != 0:
            self.tree.fail("mimo exited " + str(relay_result["returncode"]))
@@ -1107,7 +1130,7 @@ class StageExecutor:
                "artifact_hash": artifact_digest, "next_stage": next_stage,
                "artifact": artifact}

-    def _execute_qualify(self, event: dict) -> dict:
+    def _execute_qualify(self, event: dict, telemetry_attempt=None) -> dict:
        """QUALIFY (RP8/#271): implementation-readiness gate, narrowed semantics.

        Deterministic-first. The core question: is the accepted synthesis
@@ -225,3 +225,48 @@ def test_retry_does_not_overwrite_history(tree, mock_gitea):
                    "attempt": 2, "event_id": "hist-2"})
    fails_after = len([h for h in tree.state["stage_history"] if h.get("failed")])
    assert fails_after >= fails_before, "failed history must not be erased"
+
+
+# ── CORRECTION-1 (D2): producer contract + sentinel-tolerant legacy reader ───
+
+def test_reader_accepts_pure_json(tree):
+    ex = rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=1)
+    p = Path(tree.artifact_dir) / "adversarial.json"
+    p.write_text(json.dumps({"surviving_candidates": ["M1"]}))
+    assert ex._load_worker_artifact_file(str(p)) == {"surviving_candidates": ["M1"]}
+
+
+def test_reader_accepts_exact_legacy_sentinel(tree):
+    """LEGACY_COMPATIBILITY_ONLY: exactly one known sentinel tolerated."""
+    ex = rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=1)
+    p = Path(tree.artifact_dir) / "adversarial.json"
+    p.write_text(json.dumps({"surviving_candidates": ["M1"]}) + "\nStageCompleted: ADVERSARIAL\n")
+    assert ex._load_worker_artifact_file(str(p)) == {"surviving_candidates": ["M1"]}
+
+
+def test_reader_rejects_arbitrary_trailing_text(tree):
+    """No salvage: arbitrary trailing text (not the known sentinel) → JSONDecodeError."""
+    ex = rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=1)
+    p = Path(tree.artifact_dir) / "adversarial.json"
+    p.write_text(json.dumps({"surviving_candidates": ["M1"]}) + "\nsome worker chatter here\n")
+    with pytest.raises(json.JSONDecodeError):
+        ex._load_worker_artifact_file(str(p))
+
+
+def test_reader_rejects_corrupt_json(tree):
+    """Actual corruption is never masked as salvage."""
+    ex = rse.StageExecutor(issue=tree.issue, artifact_dir=tree.artifact_dir, round_no=1)
+    p = Path(tree.artifact_dir) / "adversarial.json"
+    p.write_text('{"surviving_candidates": ["M1"], truncated...')
+    with pytest.raises(json.JSONDecodeError):
+        ex._load_worker_artifact_file(str(p))
+
+
+def test_prompts_require_pure_json_artifact_file():
+    """Producer contract: every stage template states the artifact file must be
+    exactly one JSON document (markers to stdout only)."""
+    for f in (ROOT / "prompts" / "research-stages").glob("*.md"):
+        content = f.read_text()
+        if "StageCompleted:" in content:
+            assert "artifact file must contain exactly one JSON document" in content, \
+                f"{f.name}: producer contract missing"