cognitive-enhancement-engine

提供纯 Python 标准库实现的认知引擎：工作记忆 FIFO 缓存、基于 TF-IDF 倒排索引的长期记忆检索、目标分解与任务类型识别、基于记忆检索的推理、失败模式反思和元认知监控，另附 Node.js 桥接、安装脚本与测试脚本。

chen-feng123

热度 34.37

最近更新 2026-05-11 17:47:26

分类：知识依赖：代码执行应用场景：笔记整理 / 概念解释 / 工作流 / 研究

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 cognitive-enhancement-engine

Metadata

name: cognitive-enhancement-engine
description: AI Agent cognitive enhancement engine with working memory, TF-IDF vector memory, planning, reasoning, reflection, and metacognitive monitoring. Zero external dependencies. Pure Python stdlib.

Cognitive Enhancement Engine (认知力增强引擎)

Lightweight AI Agent cognitive engine with working memory, TF-IDF vector memory, planning, reasoning, reflection, and metacognitive monitoring. Zero external dependencies — pure Python standard library.

Quick Start

# Run built-in demo
python skills/cognitive-enhancement-engine/engine.py

# Or one-click setup
bash skills/cognitive-enhancement-engine/scripts/setup.sh     # Linux/macOS/WSL
skills\cognitive-enhancement-engine\scripts\setup.bat         # Windows

Core Usage

from engine import CognitiveEnhancer

# Create engine
brain = CognitiveEnhancer(long_term_capacity=1000)

# Learn
brain.memorize("Paris is the capital of France.", importance=0.9)
brain.perceive("User asked about French capital")

# Retrieve
results = brain.recall("capital of France", top_k=3)

# Plan
plan = brain.plan("Build a web application")

# Reason
answer = brain.reason("What is the capital of France?")

# Reflect
suggestions = brain.reflect()

# Full task execution
result = brain.execute_task("Calculate 15% tip on $200 bill")
print(result)

# Status
status = brain.get_status()

API Overview

Method	Description
`perceive(observation)`	Store perception into working memory
`recall(query, top_k)`	Search long-term memory
`memorize(content, importance)`	Store into long-term memory
`plan(goal)`	Decompose goal into actionable steps
`reason(problem)`	Memory-based reasoning
`reflect()`	Discover failure patterns, suggest improvements
`execute_task(goal, executor)`	End-to-end task execution
`get_status()`	Return engine runtime status

Configuration

Parameter	Default	Description
`long_term_capacity`	1000	Max long-term memories
`working_memory_size`	10	Working memory FIFO size
`similarity_threshold`	0.15	Recall similarity threshold

Features

TF-IDF Vector Memory — Inverted-index fast similarity search
Working Memory — FIFO short-term context cache
Planner — Goal decomposition + automatic task type detection (calculate/search/summarize/translate/write)
Reasoner — Memory-retrieval based Q&A
Reflector — Failure pattern tracking and root cause mining
Metacognitive Monitor — Task duration & error rate tracking, dynamic adjustment

Installation

Method	Command
One-click (Linux/macOS)	`bash scripts/setup.sh`
One-click (Windows)	`scripts\setup.bat`
Copy-only	Copy `engine.py` to your project
ClawHub	`clawhub install cognitive-enhancement-engine`

File Structure

cognitive-enhancement-engine/
├── SKILL.md
├── engine.py              # Core engine (~17KB)
├── index.js               # Node.js bridge
├── package.json
├── assets/
│   └── icon.svg
├── references/
│   ├── API_SPEC.md
│   └── USE_GUIDE.md
└── scripts/
    ├── setup.sh
    ├── setup.bat
    ├── test-basic.py
    └── test-client.js

License

MIT