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Retention Target System: auto-GC low-retention memories during consolidation (VESTIGE_RETENTION_TARGET env var, default 0.8). Auto-Promote: memories accessed 3+ times in 24h get frequency-dependent potentiation. Waking SWR Tagging: promoted memories get preferential 70/30 dream replay. Improved Consolidation Scheduler: triggers on 6h staleness or 2h active use. New tools: memory_health (retention dashboard with distribution buckets, trend tracking, recommendations) and memory_graph (subgraph export with Fruchterman-Reingold force-directed layout, up to 200 nodes). Dream connections now persist to database via save_connection(), enabling memory_graph traversal. Schema Migration V8 adds waking_tag, utility_score, times_retrieved/useful columns and retention_snapshots table. 21 MCP tools. v1.9.1 fixes: ConnectionRecord export, UTF-8 safe truncation, link_type normalization, utility_score clamping, only-new-connections persistence, 70/30 split capacity fill, nonexistent center_id error handling. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
220 lines
11 KiB
Markdown
220 lines
11 KiB
Markdown
# Vestige v1.8.0 — Cognitive Memory System
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Vestige is your long-term memory. It implements real neuroscience: FSRS-6 spaced repetition, synaptic tagging, prediction error gating, hippocampal indexing, spreading activation, and 28 stateful cognitive modules. **Use it automatically.**
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---
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## Session Start Protocol
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Every conversation, before responding to the user:
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```
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1. session_context({ → ONE CALL replaces steps 1-5
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queries: ["user preferences", "[project] context"],
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context: { codebase: "[project]", topics: ["[current topics]"] },
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token_budget: 1000
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})
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2. Check automationTriggers from response:
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- needsDream == true → call dream
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- needsBackup == true → call backup
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- needsGc == true → call gc(dry_run: true)
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- totalMemories > 700 → call find_duplicates
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```
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Say "Remembering..." then retrieve context before answering.
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> **Fallback:** If `session_context` is unavailable, use the 5-call sequence: `search` × 2 → `intention` check → `system_status` → `predict`.
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---
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## The 19 Tools
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### Context Packets (1 tool) — v1.8.0
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| Tool | When to Use |
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|------|-------------|
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| `session_context` | **One-call session initialization.** Replaces 5 separate calls (search × 2, intention check, system_status, predict) with a single token-budgeted response. Returns markdown context + `automationTriggers` (needsDream/needsBackup/needsGc) + `expandable` IDs for on-demand full retrieval. Params: `queries` (string[]), `token_budget` (100-10000, default 1000), `context` ({codebase, topics, file}), `include_status/include_intentions/include_predictions` (bool). |
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### Core Memory (1 tool)
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| Tool | When to Use |
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|------|-------------|
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| `smart_ingest` | **Default for all saves.** Single mode: provide `content` for auto-decide CREATE/UPDATE/SUPERSEDE via Prediction Error Gating. Batch mode: provide `items` array (max 20) for session-end saves — each item runs full cognitive pipeline (importance scoring, intent detection, synaptic tagging, hippocampal indexing). |
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### Unified Tools (4 tools)
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| Tool | Actions | When to Use |
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|------|---------|-------------|
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| `search` | query + filters | **Every time you need to recall anything.** Hybrid search (BM25 + semantic + convex combination fusion). 7-stage pipeline: overfetch → rerank → temporal boost → accessibility filter → context match → competition → spreading activation. Searching strengthens memory (Testing Effect). **v1.8.0:** optional `token_budget` param (100-10000) limits response size; results exceeding budget moved to `expandable` array. |
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| `memory` | get, delete, state, promote, demote | Retrieve a full memory by ID, delete a memory, check its cognitive state (Active/Dormant/Silent/Unavailable), promote (thumbs up — increases retrieval strength), or demote (thumbs down — decreases retrieval strength, does NOT delete). |
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| `codebase` | remember_pattern, remember_decision, get_context | Store and recall code patterns, architectural decisions, and project context. The killer differentiator. |
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| `intention` | set, check, update, list | Prospective memory — "remember to do X when Y happens". Supports time, context, and event triggers. |
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### Temporal (2 tools)
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| Tool | When to Use |
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|------|-------------|
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| `memory_timeline` | Browse memories chronologically. Grouped by day. Filter by type, tags, date range. When user references a time period ("last week", "yesterday"). |
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| `memory_changelog` | Audit trail. Per-memory: state transitions. System-wide: consolidations + recent changes. When debugging memory issues. |
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### Cognitive (3 tools) — v1.5.0
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| Tool | When to Use |
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|------|-------------|
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| `dream` | Trigger memory consolidation — replays recent memories to discover hidden connections and synthesize insights. At session start if >24h since last dream, after every 50 saves. |
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| `explore_connections` | Graph exploration. Actions: `chain` (reasoning path A→B), `associations` (spreading activation from a node), `bridges` (connecting memories between two nodes). When search returns 3+ related results. |
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| `predict` | Proactive retrieval — predicts what memories you'll need next based on context, activity patterns, and learned behavior. At session start, when switching projects. |
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### Auto-Save & Dedup (2 tools)
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| Tool | When to Use |
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|------|-------------|
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| `importance_score` | Score content importance before deciding whether to save. 4-channel model: novelty, arousal, reward, attention. Composite > 0.6 = worth saving. |
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| `find_duplicates` | Find near-duplicate memory clusters via cosine similarity. Returns merge/review suggestions. Run when memory count > 700 or on user request. |
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### Maintenance (5 tools)
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| Tool | When to Use |
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|------|-------------|
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| `system_status` | **Combined health + stats.** Returns status (healthy/degraded/critical/empty), full statistics, FSRS preview, cognitive module health, state distribution, warnings, and recommendations. At session start (or use `session_context` which includes this). |
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| `consolidate` | Run FSRS-6 consolidation cycle. Applies decay, generates embeddings, maintenance. At session end, when retention drops. |
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| `backup` | Create SQLite database backup. Before major upgrades, weekly. |
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| `export` | Export memories as JSON/JSONL with tag and date filters. |
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| `gc` | Garbage collect low-retention memories. When system_status shows degraded + high count. Defaults to dry_run=true. |
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### Restore (1 tool)
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| Tool | When to Use |
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|------|-------------|
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| `restore` | Restore memories from a JSON backup file. Supports MCP wrapper, RecallResult, and direct array formats. |
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### Deprecated (still work via redirects)
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| Old Tool | Redirects To |
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|----------|-------------|
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| `ingest` | `smart_ingest` |
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| `session_checkpoint` | `smart_ingest` (batch mode) |
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| `promote_memory` | `memory(action="promote")` |
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| `demote_memory` | `memory(action="demote")` |
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| `health_check` | `system_status` |
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| `stats` | `system_status` |
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---
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## Mandatory Save Gates
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**RULE: You MUST NOT proceed past a save gate without executing the save.**
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### BUG_FIX — After any error is resolved
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Your next tool call after confirming a fix MUST be `smart_ingest`:
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```
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smart_ingest({
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content: "BUG FIX: [exact error]\nRoot cause: [why]\nSolution: [what fixed it]\nFiles: [paths]",
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tags: ["bug-fix", "[project]"], node_type: "fact"
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})
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```
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### DECISION — After any architectural or design choice
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```
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codebase({
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action: "remember_decision",
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decision: "[what]", rationale: "[why]",
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alternatives: ["[A]", "[B]"], files: ["[affected]"], codebase: "[project]"
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})
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```
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### CODE_CHANGE — After writing significant code (>20 lines or new pattern)
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```
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codebase({
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action: "remember_pattern",
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name: "[pattern]", description: "[how/when to use]",
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files: ["[files]"], codebase: "[project]"
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})
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```
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### SESSION_END — Before stopping or compaction
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```
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smart_ingest({
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items: [
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{ content: "SESSION: [work done]\nFixes: [list]\nDecisions: [list]", tags: ["session-end", "[project]"] },
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// ... any unsaved fixes, decisions, patterns
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]
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})
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```
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---
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## Trigger Words — Auto-Save
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| User Says | Action |
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|-----------|--------|
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| "Remember this" / "Don't forget" | `smart_ingest` immediately |
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| "I always..." / "I never..." / "I prefer..." | Save as preference |
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| "This is important" | `smart_ingest` + `memory(action="promote")` |
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| "Remind me..." / "Next time..." | `intention` → set |
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---
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## Under the Hood — Cognitive Pipelines
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### Search Pipeline (7 stages)
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1. **Overfetch** — Pull 3x results from hybrid search (BM25 + semantic)
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2. **Reranker** — Re-score by relevance quality (cross-encoder)
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3. **Temporal boost** — Recent memories get recency bonus
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4. **Accessibility filter** — FSRS-6 retention threshold (Ebbinghaus curve)
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5. **Context match** — Tulving 1973 encoding specificity (match current context to encoding context)
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6. **Competition** — Anderson 1994 retrieval-induced forgetting (winners strengthen, competitors weaken)
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7. **Spreading activation** — Side effects: activate related memories, update predictive model, record reconsolidation opportunity
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### Ingest Pipeline (cognitive pre/post)
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**Pre-ingest:** 4-channel importance scoring (novelty/arousal/reward/attention) + intent detection → auto-tag
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**Storage:** Prediction Error Gating decides create/update/reinforce/supersede
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**Post-ingest:** Synaptic tagging (Frey & Morris 1997) + novelty model update + hippocampal indexing + cross-project recording
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### Feedback Pipeline (via memory promote/demote)
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**Promote:** Reward signal + importance boost + reconsolidation (memory becomes modifiable for 24-48h) + activation spread
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**Demote:** Competition suppression + retrieval strength decrease (does NOT delete — alternatives surface instead)
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---
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## CognitiveEngine — 28 Modules
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All modules persist across tool calls as stateful instances:
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**Neuroscience (15):** ActivationNetwork, SynapticTaggingSystem, HippocampalIndex, ContextMatcher, AccessibilityCalculator, CompetitionManager, StateUpdateService, ImportanceSignals, NoveltySignal, ArousalSignal, RewardSignal, AttentionSignal, PredictiveMemory, ProspectiveMemory, IntentionParser
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**Advanced (11):** ImportanceTracker, ReconsolidationManager, IntentDetector, ActivityTracker, MemoryDreamer, MemoryChainBuilder, MemoryCompressor, CrossProjectLearner, AdaptiveEmbedder, SpeculativeRetriever, ConsolidationScheduler
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**Search (2):** Reranker, TemporalSearcher
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---
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## Memory Hygiene
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### Promote when:
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- User confirms memory was helpful → `memory(action="promote")`
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- Solution worked correctly
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- Information was accurate
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### Demote when:
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- User corrects a mistake → `memory(action="demote")`
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- Information was wrong
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- Memory led to bad outcome
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### Never save:
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- Secrets, API keys, passwords
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- Temporary debugging state
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- Obvious/trivial information
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---
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## The One Rule
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**When in doubt, save. The cost of a duplicate is near zero (Prediction Error Gating handles dedup). The cost of lost knowledge is permanent.**
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Memory is retrieval. Searching strengthens memory. Search liberally, save aggressively.
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---
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## Development
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- **Crate:** `vestige-mcp` v1.8.0, Rust 2024 edition, Rust 1.93.1
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- **Tests:** 651 tests (313 core + 338 mcp), zero warnings
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- **Build:** `cargo build --release -p vestige-mcp`
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- **Features:** `embeddings` + `vector-search` (default on)
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- **Architecture:** `McpServer` holds `Arc<Storage>` + `Arc<Mutex<CognitiveEngine>>`
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- **Storage:** Interior mutability — `Storage` uses `Mutex<Connection>` for reader/writer split, all methods take `&self`. WAL mode for concurrent reads + writes.
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- **Entry:** `src/main.rs` → stdio JSON-RPC server
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- **Tools:** `src/tools/` — one file per tool, each exports `schema()` + `execute()`
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- **Cognitive:** `src/cognitive.rs` — 28-field struct, initialized once at startup
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