Skill: chen-feng123/quickrecall (version 1.0.5)

--- name: memory-enhancement-engine description: Persistent memory engine for AI agents with semantic recall, hotness prioritization, importance weighting, time decay, and auto-compaction. Zero external dependencies. Pure Node.js. tags: - memory - persistent - semantic-search - hotness - recall - ai-agent - nodejs features: - Hotness-prioritized recall - Semantic search (bigram + character overlap) - Importance weighting (0-2.0) - Exponential time decay - Auto-compaction and pruning - Zero external dependencies - Pure Node.js --- # Memory Enhancement Engine **记忆增加引擎** — Persistent memory engine with hotness-prioritized semantic recall. Memories that are recalled more often appear first — not just keyword matches. ## Quick Start ```bash # Node.js API const { MemorySystem } = require('./memory-enhancement-engine/memory.js'); const mem = new MemorySystem(); # CLI tool (view / search / compact) node memory-enhancement-engine/memo.cjs status node memory-enhancement-engine/memo.cjs query "something to find" ``` ## Core Usage ```javascript const { MemorySystem } = require('./memory-enhancement-engine/memory.js'); // Create engine (stores to MEMORY_STORE.json automatically) const mem = new MemorySystem({ decayHalfLifeHours: 2 }); // Write a memory mem.add({ content: "Paris is the capital of France.", importance: 1.5, metadata: { tags: ["geography", "fact"] } }); // Semantic search const results = mem.query("France capital"); console.log(results); // Get recent memories const recent = mem.recent(10); // Compact old memories (summarize low-importance clusters) mem.compact(5, 0.3); ``` ## API | Method | Description | |--------|-------------| | `add(content, importance, metadata)` | Write a memory | | `retrieve(query, k)` | Semantic search (returns sorted by score) | | `getRecent(n)` | Get N most recent memories | | `remove(predicate)` | Remove memories matching predicate | | `compact(groupSize, minImportance)` | Compact old memories into summaries | | `getStatus()` | Get engine stats (count, size, etc.) | ## Scoring Formula ``` score = similarity × 0.5 + recency × 0.3 + hotness × 0.2 ``` Where hotness = log(1 + access_count) × exp(-time_delta / 86400) ## Features - **Hotness-Prioritized Recall** — Frequently accessed memories get boosted scores - **Semantic Search** — Bigram overlap + character-level similarity - **Importance Weighting** — 0.0 (trivial) to 2.0 (critical) - **Time Decay** — Half-life configurable (default 2 hours) - **Auto-Prune** — Beyond 1000 entries, least important are pruned - **Auto-Compaction** — Merge low-importance groups into summaries - **No Server Needed** — Direct Node.js require, stores to local JSON ## Installation | Method | Command | |--------|---------| | Copy | Copy `memory.js` + `memo.cjs` to your project | | ClawHub | `clawhub install memory-enhancement-engine` | ## File Structure ``` memory-enhancement-engine/ ├── SKILL.md ├── memory.js # Core engine ├── memo.cjs # CLI tool ├── package.json ├── assets/ │ └── icon.svg ├── references/ │ ├── API_SPEC.md │ └── USE_GUIDE.md └── scripts/ ├── init-memory.mjs # One-time migration └── test-client.js ``` ## License MIT


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)