[93m[1m! [0m agent "general" is a subagent, not a primary agent. Falling back to default agent
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  \"createdAt\": \"2026-04-26T14:29:25.296Z\",\n        \"isChunk\": false,\n        \"parentId\": null,\n        \"chunkIndex\": null,\n        \"chunkLabel\": null,\n        \"chunkCount\": null,\n        \"trustBadges\": {\n          \"confidence\": 0.8,\n          \"extractionAge\": \"yesterday\",\n          \"lastAccessAge\": \"never\",\n          \"orphan\": false,\n          \"weightHistoryChanged\": false\n        },\n        \"confidence\": {\n          \"label\": \"medium\",\n          \"value\": 0.442,\n          \"drivers\": []\n        },\n        \"why\": {\n          \"summary\": \"Ranked first because semantic similarity\",\n          \"topSignals\": [\n            \"semantic_match\"\n          ]\n        }\n      }\n    ],\n    \"evidenceDigest\": \"5 results retrieved; avg score 0.71.\",\n    \"followUps\": []\n  },\n  \"hints\": [\n    \"Use includeContent: true to embed file contents in results\",\n    \"Auto-surface hook: injected 2 constitutional and 5 triggered memories (703ms)\",\n    \"Token budget enforced: truncated 5 → 1 results to fit 3500 token budget\"\n  ],\n  \"meta\": {\n    \"tool\": \"memory_search\",\n    \"tokenCount\": 3542,\n    \"latencyMs\": 575,\n    \"cacheHit\": false,\n    \"responseProfile\": \"research\",\n    \"autoSurface\": {\n      \"constitutionalCount\": 2,\n      \"triggeredCount\": 5,\n      \"surfaced_at\": \"2026-04-27T14:50:42.135Z\",\n      \"latencyMs\": 703\n    },\n    \"autoSurfacedContext\": {\n      \"constitutional\": [\n        {\n          \"id\": 2574,\n          \"specFolder\": \"system-spec-kit\",\n          \"filePath\": \"/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit/constitutional/gate-tool-routing.md\",\n          \"title\": \"TOOL ROUTING - Search & Retrieval Decision Tree\",\n          \"importanceTier\": \"constitutional\",\n          \"retrieval_directive\": \"Always surface when: TOOL ROUTING - Search & Retrieval Decision Tree | Prioritize when: task context aligns with \\\"TOOL ROUTING - Search & Retrieval Decision Tree\\\"\"\n        },\n        {\n          \"id\": 415,\n          \"specFolder\": \"system-spec-kit\",\n          \"filePath\": \"/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit/constitutional/gate-enforcement.md\",\n          \"title\": \"GATE ENFORCEMENT - Edge Cases & Cross-Reference\",\n          \"importanceTier\": \"constitutional\",\n          \"retrieval_directive\": \"Always surface when: GATE ENFORCEMENT - Edge Cases & Cross-Reference | Prioritize when: task context aligns with \\\"GATE ENFORCEMENT - Edge Cases & Cross-Reference\\\"\"\n        }\n      ],\n      \"triggered\": [\n        {\n          \"memory_id\": 825,\n          \"spec_folder\": \"00--ai-systems/001-global-shared/001-hvr-refinement-repo-analysis\",\n          \"title\": \"Feature Specification: HVR Refinement [00--ai-systems/001-global-shared/001-hvr-refinement-repo-analysis/spec]\",\n          \"matched_phrases\": [\n            \"implementation\"\n          ]\n        },\n        {\n          \"memory_id\": 2361,\n          \"spec_folder\": \"system-spec-kit/026-graph-and-context-optimization/005-code-graph/001-code-graph-upgrades\",\n          \"title\": \"Implementation [system-spec-kit/026-graph-and-context-optimization/005-code-graph/001-code-graph-upgrades/plan]\",\n          \"matched_phrases\": [\n            \"implementation\"\n          ]\n        },\n        {\n          \"memory_id\": 2221,\n          \"spec_folder\": \"system-spec-kit/024-compact-code-graph/034-workflow-split-and-token-insight-contracts\",\n          \"title\": \"Implementation Plan [system-spec-kit/024-compact-code-graph/034-workflow-split-and-token-insight-contracts/plan]\",\n          \"matched_phrases\": [\n            \"implementation\"\n          ]\n        },\n        {\n          \"memory_id\": 2215,\n 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{"type":"tool_use","timestamp":1777301443270,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6bcd15001XeSKrdRxTCab4t","messageID":"msg_dcf6b911c001WYbyim6Kjwiaix","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","type":"tool","tool":"cocoindex_code_search","callID":"call_01_d9OQo1U1HMljhZh56WSJMiRq","state":{"status":"completed","input":{"query":"search system implementation indexing","limit":8,"refresh_index":false},"output":"{\n  \"success\": true,\n  \"results\": [\n    {\n      \"file_path\": \".gemini/changelog/system-spec-kit/v2.2.4.0.md\",\n      \"language\": \"markdown\",\n      \"content\": \"This release 4-source indexing pipeline, anchor prefix matching, and 165 new tests expanding memory system to index project READMEs alongside spec files, constitutional files, and skill READMEs. It focuses on making the instructions and release notes easier for non-developers to follow. The goal is to make the workflow easier to follow and easier to trust.\\n\\n---\",\n      \"start_line\": 1,\n      \"end_line\": 3,\n      \"score\": 0.6267206328377413,\n      \"raw_score\": 0.5767206328377412,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".claude/skills/mcp-coco-index/INSTALL_GUIDE.md\",\n      \"language\": \"markdown\",\n      \"content\": \"### Performance Targets\\n\\n| Operation         | Target | Typical   |\\n| ----------------- | ------ | --------- |\\n| Semantic search   | <2s    | ~500ms    |\\n| Index build       | varies | 1-5 min   |\\n| Index refresh     | <30s   | ~10s      |\\n| Status check      | <1s    | ~200ms    |\\n\\n<!-- /ANCHOR:overview -->\\n\\n---\\n\\n<!-- ANCHOR:prerequisites -->\",\n      \"start_line\": 158,\n      \"end_line\": 171,\n      \"score\": 0.606388769624375,\n      \"raw_score\": 0.556388769624375,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/feature_catalog/feature_catalog.md\",\n      \"language\": \"markdown\",\n      \"content\": \"### Hybrid search pipeline\\n\\n#### Description\\n\\nWhen you search for something, the system looks in several places at once, like checking both the index and the shelves in a library. It then combines all the results and ranks them by relevance so the best match shows up first. If the first search comes back empty, the system automatically widens its net and tries again with looser criteria so you almost never get zero results.\",\n      \"start_line\": 277,\n      \"end_line\": 281,\n      \"score\": 0.6044510688343661,\n      \"raw_score\": 0.554451068834366,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/references/memory/memory_system.md\",\n      \"language\": \"markdown\",\n      \"content\": \"### Core Capabilities\\n\\n- **Semantic search** - Find indexed spec-doc records by meaning, not just keywords\\n- **Importance tiers** - Six-level system for prioritizing context\\n- **Decay scoring** - Recent indexed spec-doc records rank higher than older ones\\n- **Checkpoints** - Save/restore indexed-continuity state snapshots\\n- **Constitutional tier** - Critical rules that always surface\",\n      \"start_line\": 30,\n      \"end_line\": 36,\n      \"score\": 0.6026304841953742,\n      \"raw_score\": 0.5526304841953742,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/mcp_server/lib/search/folder-discovery.ts\",\n      \"language\": \"typescript\",\n      \"content\": \"// 5. RELEVANCE SCORING / LOOKUP\\n// ───────────────────────────────────────────────────────────────\\n\\n/**\\n * Find the most relevant spec folders for a given query using\\n * simple keyword-overlap scoring.\\n *\\n * Algorithm:\\n * - Tokenize the query into lowercase words (reuse extractKeywords)\\n * - For each folder in the cache, count how many query terms appear\\n *   in its keywords or description (case-insensitive)\\n * - Normalize score: matchCount / totalQueryTerms\\n * - Return top `limit` folders with score > 0, sorted descending\\n *\\n * This is a lightweight pre-filter, NOT a replacement for vector search.\\n *\\n * @param query  - User search query string.\\n * @param cache  - Loaded DescriptionCache to search against.\\n * @param limit  - Maximum number of results to return (default 3).\\n * @returns Array of { specFolder, relevanceScore } sorted by score desc.\\n */\",\n      \"start_line\": 527,\n      \"end_line\": 547,\n      \"score\": 0.5976786084931842,\n      \"raw_score\": 0.5476786084931842,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/feature_catalog/14--pipeline-architecture/08-performance-improvements.md\",\n      \"language\": \"markdown\",\n      \"content\": \"# Performance improvements\\n\\n## 1. OVERVIEW\\n\\nSixteen performance improvements reduce runtime cost across TF-IDF scoring, fallback fusion, token budgeting, mutation ledger scanning, entity linking and hierarchy caching.\\n\\nSixteen small speed improvements were made across the system. Some replaced slow scanning operations with faster lookups. Others fixed places where the same question was asked many times when once would do. The result is a system that responds more quickly, especially as the amount of stored data grows. Think of it as replacing a hand-cranked search with a power tool.\\n\\n---\",\n      \"start_line\": 7,\n      \"end_line\": 15,\n      \"score\": 0.5972090803136478,\n      \"raw_score\": 0.5472090803136478,\n      \"path_class\": \"implementation\",\n      \"rankingSignals\": [\n        \"implementation_boost\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/mcp_server/README.md\",\n      \"language\": \"markdown\",\n      \"content\": \"## 3. FEATURES\\n\\n### 3.1 HOW THE INDEXED-CONTINUITY STORE WORKS\\n\\nThis section explains the main ideas behind the indexed-continuity store in plain language. For the full tool reference with parameters, skip to [3.2 Tool Reference](#32-tool-reference).\\n\\n---\\n\\n#### 3.1.1 HYBRID SEARCH\\n\\nWhen you search for something, the system checks several sources at once. Think of a librarian who checks the card catalog, the shelf labels, the reading room sign-out sheet and the recommendation board all at the same time.\\n\\n**Five core search channels** work together, with **CocoIndex** available as an external semantic code search bridge:\",\n      \"start_line\": 233,\n      \"end_line\": 245,\n      \"score\": 0.5230214294922007,\n      \"raw_score\": 0.5730214294922007,\n      \"path_class\": \"docs\",\n      \"rankingSignals\": [\n        \"docs_penalty\"\n      ]\n    },\n    {\n      \"file_path\": \".gemini/skills/system-spec-kit/README.md\",\n      \"language\": \"markdown\",\n      \"content\": \"#### Evaluation Infrastructure\\n\\nThe indexed-continuity store includes built-in tools for measuring search quality:\\n\\n- **Ablation studies** -- turn off one search component at a time to measure its contribution, like removing one ingredient from a recipe to see if the dish still tastes good\\n- **12-metric computation** -- MRR, NDCG, MAP and 9 other information retrieval metrics\\n- **Synthetic ground truth corpus** -- 110 test questions with known correct answers for benchmarking, keyed to live parent-memory IDs; rerun `scripts/evals/map-ground-truth-ids.ts` after DB rebuilds or imports before trusting ablation or reporting comparisons\\n- **Reporting dashboard** -- performance trends across work periods and search channels, sourced from parent-memory-normalized eval rows even when retrieval hits came from chunks\\n\\n---\\n\\n<!-- divider:4.3 -->\",\n      \"start_line\": 437,\n      \"end_line\": 448,\n      \"score\": 0.522811657060356,\n      \"raw_score\": 0.5728116570603561,\n      \"path_class\": \"docs\",\n      \"rankingSignals\": [\n        \"docs_penalty\"\n      ]\n    }\n  ],\n  \"total_returned\": 8,\n  \"offset\": 0,\n  \"dedupedAliases\": 23,\n  \"uniqueResultCount\": 8,\n  \"message\": null\n}","metadata":{"truncated":false},"title":"","time":{"start":1777301443061,"end":1777301443270},"attachments":[]}}}
{"type":"tool_use","timestamp":1777301445231,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6bd2ef001GmPTVbEISeHjWg","messageID":"msg_dcf6b911c001WYbyim6Kjwiaix","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","type":"tool","tool":"grep","callID":"call_02_KmybxR3O9IREI9m17srq2Zgc","state":{"status":"completed","input":{"pattern":"search|Search","include":"SKILL.md","path":"/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit"},"output":"Found 31 matches\n/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit/SKILL.md:\n  Line 8: <!-- Keywords: spec-kit, speckit, documentation-workflow, spec-folder, template-enforcement, context-preservation, progressive-documentation, validation, spec-kit-memory, vector-search, hybrid-search, bm25, rrf-fusion, fsrs-decay, constitutional-tier, checkpoint, importance-tiers, cognitive-memory, co-activation, tiered-injection -->\n  Line 26: - **Contents**: Markdown files (spec.md, plan.md, tasks.md, and implementation-summary.md when work is complete) plus optional support folders such as `scratch/`, `research/`, or `review/`\n  Line 63: Any agent writing authored spec folder docs (`spec.md`, `plan.md`, `tasks.md`, `checklist.md`, `implementation-summary.md`, `decision-record.md`, `handover.md`, `review-report.md`, `debug-delegation.md`, `resource-map.md` (optional)) MUST use templates from .opencode/skills/system-spec-kit/templates/level_N/ for level-owned docs and the root cross-cutting templates where applicable, run `bash .opencode/skills/system-spec-kit/scripts/spec/validate.sh [spec_folder] --strict` after each file write, and route continuity updates through /memory:save. Deep-research workflow-owned packet markdown (`research/iterations/*.md`, `research/deep-research-*.md`, and progressive `research/research.md` loop updates) is exempt from that generic per-write rule; `/spec_kit:deep-research` must instead run targeted strict validation after every `spec.md` mutation it performs. @deep-research retains exclusive write access for `research/research.md`; @debug retains exclusive write access for `debug-delegation.md`.\n  Line 122: `references/workflows/quick_reference.md` is the primary first-touch command surface. Keep the compact `spec_kit` and `memory` command map there, including `/spec_kit:plan --intake-only` as the standalone intake entry, `/spec_kit:plan` and `/spec_kit:complete` smart delegation notes, and the pointer from `/spec_kit:deep-research` to `../sk-deep-research/references/spec_check_protocol.md`, and use this file only to point readers to it rather than duplicating the full matrix.\n  Line 144:     \"RETRIEVAL_TUNING\": {\"weight\": 3, \"keywords\": [\"retrieval\", \"search tuning\", \"fusion\", \"scoring\", \"pipeline\"]},\n  Line 215:     \"/memory:search\": \"MEMORY\",\n  Line 538: # Bare child name (auto-searches all parents for unique match)\n  Line 550: Canonical routed saves use the live 8-category content router: `narrative_progress`, `narrative_delivery`, `decision`, `handover_state`, `research_finding`, `task_update`, `metadata_only`, and `drop`. Tier 3 LLM routing is part of the live save handler by default: when `LLM_REFORMULATION_ENDPOINT` is reachable and returns a usable decision, it participates automatically; otherwise saves stay on Tier 1/Tier 2 routing with safe fallback or refusal. Delivery routing now keys off sequencing, gating, rollout, and verification language, handover stays reserved for stop-state and resume instructions, and hard transcript/tool telemetry still routes to `drop`. `routeAs` may force a category and preserve the natural decision for audit, while `packet_kind` is derived from spec metadata first with parent-phase fallback only when metadata is silent. See [save_workflow.md](./references/memory/save_workflow.md) for the detailed routing contract.\n  Line 553: For research trees, `scripts/memory/backfill-research-metadata.ts` fills in missing `description.json` and `graph-metadata.json` files under `research/*/iterations/` without rewriting folders that are already complete.\n  Line 573: **Memory Commands:** 4 memory slash commands (`/memory:save`, `/memory:manage`, `/memory:learn`, `/memory:search`) cover the spec-doc record command surface, while `/spec_kit:resume` owns session recovery through the broader memory/session recovery stack. The `spec_kit` surface now uses `/spec_kit:plan --intake-only` as the standalone intake workflow; `/spec_kit:plan` and `/spec_kit:complete` execute the shared intake contract (`.opencode/skills/system-spec-kit/references/intake-contract.md`) inline when the Step 0 local `folder_state` shows repair or creation is needed, and downstream callers should consume the contract's canonical `start_state` rather than reusing the local classifier name. `/spec_kit:deep-research` follows `../sk-deep-research/references/spec_check_protocol.md` for bounded `spec.md` anchoring. The `/memory:search` command covers all analysis and retrieval workflows. See `.opencode/commands/memory/`, `.opencode/commands/spec_kit/plan.md`, `.opencode/commands/spec_kit/complete.md`, `.opencode/skills/system-spec-kit/references/intake-contract.md`, and `.opencode/commands/spec_kit/resume.md` for command documentation.\n  Line 580: | `memory_search()`               | L2    | 5-channel hybrid retrieval with intent-aware routing, channel normalization, graph/degree signals, reranking, and filtered output |\n  Line 581: | `memory_quick_search()`         | L2    | Simplified search (query + optional spec folder)  |\n  Line 594: > **Search architecture:** The search pipeline uses a 4-stage architecture (candidate generation → fusion → reranking → filtering). Current retrieval uses five channels, normalizes fallback thresholds correctly, keeps disabled channels disabled through fallback, defers irreversible confidence truncation until after reranking, and enforces token budgets using actual post-truncation counts. Adaptive fusion includes an internal continuity profile (`semantic 0.52`, `keyword 0.18`, `recency 0.07`, `graph 0.23`), Stage 3 uses a minimum rerank gate of 4 candidates, the retained `applyLengthPenalty` input is a compatibility no-op, and `getRerankerStatus()` exposes reranker cache hits, misses, stale hits, and evictions. See [search/README.md](./mcp_server/lib/search/README.md) for pipeline details, scoring algorithms, and graph signal features.\n  Line 605: **memory_search() - Key Rules:**\n  Line 624: - **Constitutional tier** - 3.0x search boost + 2.0x importance multiplier; merged into normal scoring pipeline\n  Line 634: - **Artifact routing** - 9 artifact classes (spec, plan, tasks, checklist, decision-record, implementation-summary, memory, research, unknown) with per-type retrieval strategies applied at query time\n  Line 639: - **Runtime-resolved flags** - Long-lived MCP processes re-read rollout and scoring flags at runtime for graph-walk rollout, co-activation, relation handling, and related search toggles instead of freezing values at import time\n  Line 650: - **Memory causal trust display badges (012/005)** - `memory_search` results now carry an additive `trustBadges` payload per `MemoryResultEnvelope`: `confidence` from edge `strength`, `extractionAge`, `lastAccessAge`, `orphan` (no incoming edges), `weightHistoryChanged` (any connected edge has a `weight_history` row). Display-only — derived at response time from existing causal-edge columns; no schema change, no new relation types, no new storage of code/process/tool facts. Response profiles (`quick`, `research`, `resume`) preserve the badge payload on `results[]` and `topResult` (ADR-012-005)\n  Line 659: | `SPECKIT_ADAPTIVE_FUSION`     | on      | Enables intent-aware weighted RRF in `memory_search()`, including the internal continuity profile used for resume-style retrieval (set `false` to disable) |\n  Line 666: | `SPECKIT_LEARN_FROM_SELECTION` | on    | Tracks which search results are used and boosts them in future searches |\n  Line 667: | `SPECKIT_EMBEDDING_EXPANSION` | on     | Expands queries with semantic neighbors before vector search |\n  Line 669: | `SPECKIT_ENTITY_LINKING`     | on      | Links memories sharing extracted entities during search |\n  Line 687: | `SPECKIT_EMPTY_RESULT_RECOVERY_V1` | on | Structured recovery payloads for empty/weak search results |\n  Line 692: | `SPECKIT_RESPONSE_PROFILE_V1` | on     | Mode-aware response profiles: quick, research, resume, debug |\n  Line 800: **Query routing:** Structural queries (callers, imports, deps) -> `code_graph_query`. Semantic/concept queries -> CocoIndex (`mcp__cocoindex_code__search`). Session/memory queries -> `memory_context`.\n  Line 802: **CocoIndex seed bridge:** CocoIndex search results (file + line range) are accepted as seeds by `code_graph_context`, which resolves them to graph nodes and expands structurally. This combines \"what resembles what\" (CocoIndex) with \"what connects to what\" (Code Graph).\n  Line 810: | `ccc_feedback` | Submit quality feedback on search results |\n  Line 832: 5. **Check for related specs before creating new folders** - Search keywords, review status\n  Line 846: 19. **Enforce ToC policy from validation rules** - Only `research/research.md` may include a Table of Contents section; remove ToC headings from standard spec artifacts\n  Line 888: - [ ] No ToC heading in non-research spec artifacts (ToC allowed only in `research/research.md`, including `resource-map.md` when present)\n  Line 963: Canonical command lifecycle: `/spec_kit:plan --intake-only` establishes or repairs the packet when standalone intake is needed, `/spec_kit:deep-research` follows `../sk-deep-research/references/spec_check_protocol.md` when research needs bounded `spec.md` anchoring, and `/spec_kit:plan` or `/spec_kit:complete` continue from the same folder while reusing the shared intake contract (`.opencode/skills/system-spec-kit/references/intake-contract.md`) only when the local `folder_state` still needs repair. When intake runs, the returned `start_state` is the canonical downstream field.","metadata":{"matches":31,"truncated":false},"title":"search|Search","time":{"start":1777301445204,"end":1777301445229}}}}
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{"type":"tool_use","timestamp":1777301454004,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6bf527001hHHi8WWyXSVLA7","messageID":"msg_dcf6bdded001hEdnX2hqXCkf35","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","type":"tool","tool":"read","callID":"call_00_xSPJKiNvMo5qMfI3pc9NO63R","state":{"status":"completed","input":{"filePath":"/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit/mcp_server/lib/search/README.md","limit":100},"output":"<path>/Users/michelkerkmeester/MEGA/Development/Code_Environment/Public/.opencode/skills/system-spec-kit/mcp_server/lib/search/README.md</path>\n<type>file</type>\n<content>\n1: ---\n2: title: \"Search Subsystem\"\n3: description: \"5-channel hybrid search architecture combining vector, lexical (BM25/FTS5), graph-based and structure-aware graph retrieval with Reciprocal Rank Fusion (RRF) and Adaptive Fusion.\"\n4: trigger_phrases:\n5:   - \"search subsystem\"\n6:   - \"hybrid search\"\n7:   - \"vector search\"\n8: ---\n9: \n10: # Search Subsystem\n11: \n12: > 5-channel hybrid search architecture combining vector, lexical (BM25/FTS5), graph-based and structure-aware graph retrieval, fused with Reciprocal Rank Fusion (RRF) and Adaptive Fusion.\n13: \n14: ---\n15: \n16: ## TABLE OF CONTENTS\n17: <!-- ANCHOR:table-of-contents -->\n18: \n19: - [1. OVERVIEW](#1-overview)\n20:   - [4-STAGE PIPELINE ARCHITECTURE](#4-stage-pipeline-architecture)\n21: - [2. KEY CONCEPTS](#2-key-concepts)\n22: - [3. MODULE STRUCTURE](#3-module-structure)\n23: - [4. FEATURES](#4-features)\n24:   - [GRAPH SIGNAL FEATURES](#graph-signal-features)\n25:   - [SAVE-TIME PROCESSING PIPELINE](#save-time-processing-pipeline)\n26:   - [SCORING ENHANCEMENTS](#scoring-enhancements)\n27: - [FTS CAPABILITY CASCADE FLOOR](#fts-capability-cascade-floor)\n28: - [5. USAGE EXAMPLES](#5-usage-examples)\n29: - [6. RECENT CHANGES (SPRINT 8)](#6-recent-changes-sprint-8)\n30: - [7. RELATED RESOURCES](#7-related-resources)\n31: \n32: <!-- /ANCHOR:table-of-contents -->\n33: \n34: ---\n35: \n36: ## 1. OVERVIEW\n37: <!-- ANCHOR:overview -->\n38: \n39: The search subsystem provides production-grade hybrid search capabilities with multiple retrieval methods fused via RRF scoring. It handles query expansion, intent classification, typo tolerance and optional cross-encoder reranking.\n40: \n41: Gate E alignment: retrieval is subordinate to the canonical continuity chain. Resume and continuity work should anchor on `/spec_kit:resume`, then rebuild context from `handover.md -> _memory.continuity -> spec docs`. Search helps rank supporting evidence after those source-of-truth surfaces are known.\n42: \n43: **Core Capabilities:**\n44: - **5-Channel Hybrid Search**: Vector (semantic) + BM25/FTS5 (lexical) + Graph (relationship-based) + Graph Structure (structural)\n45: - **RRF Score Fusion**: Industry-standard k=40 with convergence bonuses\n46: - **Intent Classification**: 7 intent types route to task-specific retrieval weights\n47: - **Query Enhancement**: Fuzzy matching (Levenshtein) + acronym expansions (via hybrid-search.ts inline logic)\n48: - **Reranking Pipeline**: Optional cross-encoder with length penalties\n49: - **MMR Diversity Reranking**: Maximal Marginal Relevance to reduce redundancy in result sets\n50: - **Evidence Gap Detection**: Identifies missing context and suggests follow-up queries\n51: - **Schema Management**: sqlite-vec schema v15 (current) with document-type fields, event-based decay and phase-aware columns\n52: \n53: **Architecture Pattern:**\n54: ```text\n55: Query Input\n56:     |\n57: Intent Classifier -> Task-specific weights\n58:     |\n59: Parallel Search (5 channels)\n60: |---> Vector (sqlite-vec)       -> Semantic matches\n61: |---> BM25 (Pure JS)            -> Keyword matches\n62: |---> Graph (Co-activation)     -> Relationship matches\n63: |---> Graph Structure           -> Structural matches\n64:     |\n65: RRF Fusion (k=40) + Adaptive Fusion -> Unified scores\n66:     |\n67: MMR Diversity Reranking -> Redundancy reduction\n68:     |\n69: Cross-Encoder Rerank (optional) -> Relevance refinement\n70:     |\n71: Recency Boost + Co-activation -> Final adjustments\n72:     |\n73: Final Results\n74: ```\n75: \n76: **Architecture Note:**\n77: `vector-index.ts` is the primary typed export surface for the vector index and re-exports the split schema, query, mutation, store and alias modules. `vector-index-impl.ts` is now a 14-line backward-compatibility shim that simply re-exports `vector-index.ts` for older import paths.\n78: \n79: <a id=\"4-stage-pipeline-architecture\"></a>\n80: ### 4-Stage Pipeline Architecture\n81: \n82: The search pipeline (R6) decomposes retrieval into four bounded stages with strict responsibilities. Each stage has clear input/output contracts defined in `pipeline/types.ts`.\n83: \n84: ```text\n85: Stage 1                Stage 2                 Stage 3              Stage 4\n86: CANDIDATE GEN    -->   FUSION + SIGNALS   -->  RERANK + AGGREGATE  -->  FILTER + ANNOTATE\n87: (no score changes)     (single scoring point)  (score changes: YES)    (score changes: NO)\n88: ```\n89: \n90: **Stage 1 — Candidate Generation** (`stage1-candidate-gen.ts`):\n91: Executes 5 search channels in parallel and collects raw candidates with no scoring modifications.\n92: \n93: | Channel | Source | Description |\n94: |---------|--------|-------------|\n95: | Vector | `vector-index.ts` | Semantic similarity via sqlite-vec through the split vector-index modules |\n96: | BM25 | `bm25-index.ts` | Pure TypeScript keyword matching |\n97: | FTS5 | `sqlite-fts.ts` | SQLite FTS5 BM25 weighted scoring |\n98: | Graph | `graph-search-fn.ts` | Causal edge traversal + typed-weighted degree (R4) |\n99: | Degree | `graph-search-fn.ts` | Structural graph discovery via typed-weighted degree |\n100: \n\n(Showing lines 1-100 of 977. Use offset=101 to continue.)\n</content>","metadata":{"preview":"---\ntitle: \"Search Subsystem\"\ndescription: \"5-channel hybrid search architecture combining vector, lexical (BM25/FTS5), graph-based and structure-aware graph retrieval with Reciprocal Rank Fusion (RRF) and Adaptive Fusion.\"\ntrigger_phrases:\n  - \"search subsystem\"\n  - \"hybrid search\"\n  - \"vector search\"\n---\n\n# Search Subsystem\n\n> 5-channel hybrid search architecture combining vector, lexical (BM25/FTS5), graph-based and structure-aware graph retrieval, fused with Reciprocal Rank Fusion (RRF) and Adaptive Fusion.\n\n---\n\n## TABLE OF CONTENTS\n<!-- ANCHOR:table-of-contents -->\n\n- [1. OVERVIEW](#1-overview)\n  - [4-STAGE PIPELINE ARCHITECTURE](#4-stage-pipeline-architecture)","truncated":true,"loaded":[]},"title":".opencode/skills/system-spec-kit/mcp_server/lib/search/README.md","time":{"start":1777301453993,"end":1777301454004}}}}
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Consider first principles.**\",\n    \"intent\": {\n      \"type\": \"understand\",\n      \"confidence\": 1,\n      \"description\": \"Understanding or exploring the codebase\",\n      \"weightsApplied\": \"off\"\n    },\n    \"artifactRouting\": {\n      \"strategy\": {\n        \"artifactClass\": \"research\",\n        \"semanticWeight\": 0.7,\n        \"keywordWeight\": 0.3,\n        \"recencyBias\": 0.2,\n        \"maxResults\": 5,\n        \"boostFactor\": 1\n      },\n      \"detectedClass\": \"research\",\n      \"confidence\": 0.3333333333333333\n    },\n    \"artifact_routing\": {\n      \"strategy\": {\n        \"artifactClass\": \"research\",\n        \"semanticWeight\": 0.7,\n        \"keywordWeight\": 0.3,\n        \"recencyBias\": 0.2,\n        \"maxResults\": 5,\n        \"boostFactor\": 1\n      },\n      \"detectedClass\": \"research\",\n      \"confidence\": 0.3333333333333333\n    },\n    \"graphContribution\": {\n      \"killSwitchActive\": false,\n      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ENFORCEMENT - Edge Cases & Cross-Reference\",\n          \"importanceTier\": \"constitutional\",\n          \"retrieval_directive\": \"Always surface when: GATE ENFORCEMENT - Edge Cases & Cross-Reference | Prioritize when: task context aligns with \\\"GATE ENFORCEMENT - Edge Cases & Cross-Reference\\\"\"\n        }\n      ],\n      \"triggered\": [\n        {\n          \"memory_id\": 1506,\n          \"spec_folder\": \"system-spec-kit/022-hybrid-rag-fusion/008-hydra-db-based-features\",\n          \"title\": \"Decision Record: 008-hydra-db-ba [system-spec-kit/022-hybrid-rag-fusion/008-hydra-db-based-features/decision-record]\",\n          \"matched_phrases\": [\n            \"architecture\"\n          ]\n        },\n        {\n          \"memory_id\": 1421,\n          \"spec_folder\": \"system-spec-kit/022-hybrid-rag-fusion/007-code-audit-per-feature-catalog/014-pipeline-architecture\",\n          \"title\": \"Feature 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{"type":"step_finish","timestamp":1777301458421,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6c0d260014tArUMN24Vv8S2","reason":"tool-calls","snapshot":"01fdcefd9f7200da5637528ee29307c95c6935e7","messageID":"msg_dcf6bdded001hEdnX2hqXCkf35","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","type":"step-finish","tokens":{"total":48879,"input":15992,"output":197,"reasoning":50,"cache":{"write":0,"read":32640}},"cost":0.02915892}}
{"type":"step_start","timestamp":1777301463002,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6c1fd6001SOBAb5OOI7YvzZ","messageID":"msg_dcf6c0ec0001kIFNGWgqOe29xv","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","snapshot":"7c371a602b98546f7935414ca9037648c467f0e1","type":"step-start"}}
{"type":"text","timestamp":1777301486693,"sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","part":{"id":"prt_dcf6c234e001wcV8sOS9ozA7Y2","messageID":"msg_dcf6c0ec0001kIFNGWgqOe29xv","sessionID":"ses_2309471a6ffeUfiXf6sZN5mIym","type":"text","text":"Here's a concise summary of the search system:\n\n---\n\n## Search System — Spec Kit Memory\n\n**Location:** `.opencode/skills/system-spec-kit/mcp_server/lib/search/` (74 TS files)  \n**Key docs:** `lib/search/README.md` (977 lines), `.opencode/skills/system-spec-kit/SKILL.md` (§3-6)\n\n### Architecture: 4-Stage / 5-Channel Pipeline\n\n```\nQuery → Intent Classify → [5 channels parallel] → RRF Fusion → MMR Diversity → Cross-Encoder Rerank → Filter → Results\n```\n\n**4 pipeline stages** (`pipeline/`):\n1. **Candidate Gen** (`stage1-candidate-gen.ts`) — 5 channels, no scoring\n2. **Fusion + Signals** (`stage2-fusion.ts`, `stage2b-enrichment.ts`) — single scoring point via RRF\n3. **Rerank + Aggregate** (`stage3-rerank.ts`) — cross-encoder, chunk reassembly\n4. **Filter + Annotate** (`stage4-filter.ts`) — token budget, state filtering, evidence gaps\n\n**5 channels** (Stage 1):\n| Channel | Source | What |\n|---------|--------|------|\n| Vector | `vector-index.ts` → sqlite-vec | Semantic similarity |\n| BM25 | `bm25-index.ts` | Pure TS keyword scoring |\n| FTS5 | `sqlite-fts.ts` | SQLite FTS5 lexical |\n| Graph | `graph-search-fn.ts` | Causal edge traversal + co-activation |\n| Degree/Structure | `graph-search-fn.ts` | Typed-weighted graph degree |\n\n### Key Modules\n\n- **`hybrid-search.ts`** — Main orchestrator, query expansion, reranking\n- **`intent-classifier.ts`** — 7 intent types routed to task-specific weights\n- **`cross-encoder.ts`** / **`reranker.ts`** — Cross-encoder and MMR diversity reranking\n- **`causal-boost.ts`** / **`session-boost.ts`** — Two boost systems\n- **`fsrs.ts`** — Temporal decay scoring (spaced repetition model)\n- **`artifact-routing.ts`** — 9 artifact classes with per-type retrieval strategies\n- **`confidence-scoring.ts`** / **`confidence-truncation.ts`** — Confidence gates\n- **`evidence-gap-detector.ts`** — Detects missing context, suggests follow-ups\n- **`progressive-disclosure.ts`** — Summary → detail result layering\n- **`embedding-expansion.ts`** — Semantic query expansion pre-vector search\n- **`entity-linker.ts`** — Links results sharing extracted entities\n\n### Tools Exposed to AI\n\n- `memory_search()` — Full hybrid search (L2 core)\n- `memory_quick_search()` — Simplified wrapper\n- `memory_context()` — Unified context retrieval with intent routing\n- `memory_match_triggers()` — Fast trigger phrase matching\n\n### External: CocoIndex\n\nSeparate semantic code search via `.opencode/skills/mcp-coco-index/` — `cocoindex_code_search()` MCP tool, used when Grep/Glob exact matches are insufficient.\n\n### Spec Folders (history)\n\n- `system-spec-kit/022-hybrid-rag-fusion/` — Hybrid RAG fusion phases\n- `system-spec-kit/023-hybrid-rag-fusion-refinement/` — Refinement, FTS5 fixes, dashboards\n- `system-spec-kit/024-compact-code-graph/` — FTS forced-degrade, cached summaries","time":{"start":1777301486691,"end":1777301486691}}}
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