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QuickRecall - Zero-Dependency Memory Engine. 常用记忆优先出现。零依赖 AI 记忆引擎,纯 Node.js。/ Prioritizes frequently used memories. Zero deps.

该 Skill 是纯 Node.js 的本地记忆引擎,支持写入带重要度和标签的记忆、基于二元组与字符重叠的语义检索、热度与时间衰减评分,以及低重要度记忆的自动压缩;数据保存在本地 JSON 文件中,可通过 CLI 查看、搜索和压缩。

chen-feng123
chen-feng123
热度 49.70
最近更新 2026-05-11 17:47:10
分类:知识依赖:代码执行 / 读写文件应用场景:笔记整理 / 摘要总结 / 工作流

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add quickrecall
Metadata
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

# 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

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