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+---
+name: Self-Evolving Skill
+description: "元认知自我学习系统——自动技能进化。"
+homepage: https://github.com/whtoo/self-evolving-bot
+
+---
+
+
+# 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
+
+```bash
+# 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
+
+```bash
+# 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
+
+```bash
+# 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
+
+```typescript
+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
+
+```python
+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
+
+```python
+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](./README.md) - 完整文档
+- [MCP_CONFIG.md](./MCP_CONFIG.md) - MCP配置说明
+- [MEMORY.md](../MEMORY.md) - 研究笔记