Meta-cognitive self-learning system - Automated skill evolution based on predictive coding and value-driven mechanisms.
Self-Evolving Skill
元认知自学习系统 - 基于预测编码和价值驱动的Skill自动演化。
功能
ResidualPyramid金字塔分解,量化认知缺口
-: 残差 自适应反思触发: 基于残差能量自动判断何时需要学习
经验回放: 缓存已学模式,降低重复触发
价值门控: 只有提升长期价值才接受变异
持久化: 经验自动保存/加载
安装
# 技能已安装到 ~/.openclaw/skills/self-evolving-skill
# 或使用ClawHub
clawhub install self-evolving-skill
架构
self-evolving-skill/
├── core/ # Python核心
│ ├── residual_pyramid.py # 残差金字塔(SVD分解)
│ ├── reflection_trigger.py # 自适应触发器
│ ├── experience_replay.py # 经验回放缓存
│ ├── skill_engine.py # 核心引擎+ValueGate
│ ├── storage.py # 持久化
│ └── mcp_server.py # MCP服务器
├── src/ # TypeScript SDK
│ ├── index.ts # 主入口
│ ├── cli.ts # CLI
│ └── mcp-tools.ts # 工具定义
├── skills/ # OpenClaw Skill
│ └── self-evolving-skill/ # 技能封装
├── MCP_CONFIG.md # MCP配置
└── README.md # 文档
MCP工具
工具
描述
参数
skill_create
创建Skill
name, description
skill_execute
执行并学习
skill_id, context, success, value
skill_analyze
分析嵌入
embedding
skill_list
列出Skills
-
skill_stats
系统统计
-
skill_save
持久化保存
skill_id
skill_load
加载
skill_id
使用方式
CLI
# 列出所有Skill
openclaw skill self-evolving-skill list
# 创建Skill
openclaw skill self-evolving-skill create --name "MySkill"
# 执行
openclaw skill self-evolving-skill execute <id> --success
# 分析
openclaw skill self-evolving-skill analyze --embedding '[0.1,0.2,...]'
# 统计
openclaw skill self-evolving-skill stats
MCP服务器
# 启动MCP服务器
cd ~/.openclaw/skills/self-evolving-skill
./run_mcp.sh
# 或使用适配器
python3 mcporter_adapter.py skill_list '{}'
编程
import { SelfEvolvingSkillEngine } from 'self-evolving-skill';
const engine = new SelfEvolvingSkillEngine();
await engine.init();
const { skillId } = await engine.createSkill({ name: 'Analyzer' });
const stats = await engine.stats();
核心算法
1. 残差金字塔分解
pyramid = ResidualPyramid(max_layers=5, use_pca=True)
decomposition = pyramid.decompose(embedding)
# 输出:
# - residual_ratio: 残差能量比率
# - suggested_abstraction: POLICY / SUB_SKILL / PREDICATE
# - novelty_score: 综合新颖性
2. 三层跃迁规则
覆盖率
抽象层级
操作
>80%
POLICY
调整策略权重
40-80%
SUB_SKILL
生成子Skill
<40%
PREDICATE
归纳新谓词
3. 自适应阈值
trigger = ReflectionTrigger(
min_energy_ratio=0.10, # 初始阈值
value_gain_threshold=0.20, # 触发阈值
target_trigger_rate=0.15 # 目标15%触发率
)
文件位置
路径
说明
~/.openclaw/skills/self-evolving-skill
技能根目录
~/.openclaw/mcp_servers/self-evolving-skill.json
MCP服务器配置
~/.openclaw/workspace/self-evolving-skill/storage
数据存储
相关文档
README.md - 完整文档
MCP_CONFIG.md - MCP配置说明
MEMORY.md - 研究笔记don't have the plugin yet? install it then click "run inline in claude" again.