skill-evolution-manager

3
0
Source

专门用于在对话结束时,根据用户反馈和对话内容总结优化并迭代现有 Skills 的核心工具。它通过吸取对话中的“精华”(如成功的解决方案、失败的教训、特定的代码规范)来持续演进 Skills 库。

Install

mkdir -p .claude/skills/skill-evolution-manager && curl -L -o skill.zip "https://mcp.directory/api/skills/download/3118" && unzip -o skill.zip -d .claude/skills/skill-evolution-manager && rm skill.zip

Installs to .claude/skills/skill-evolution-manager

About this skill

Skill Evolution Manager

这是整个 AI 技能系统的“进化中枢”。它不仅负责优化单个 Skill,还负责跨 Skill 的经验复盘和沉淀。

核心职责

  1. 复盘诊断 (Session Review):在对话结束时,分析所有被调用的 Skill 的表现。
  2. 经验提取 (Experience Extraction):将非结构化的用户反馈转化为结构化的 JSON 数据(evolution.json)。
  3. 智能缝合 (Smart Stitching):将沉淀的经验自动写入 SKILL.md,确保持久化且不被版本更新覆盖。

使用场景

Trigger:

  • /evolve
  • "复盘一下刚才的对话"
  • "我觉得刚才那个工具不太好用,记录一下"
  • "把这个经验保存到 Skill 里"

工作流 (The Evolution Workflow)

1. 经验复盘 (Review & Extract)

当用户触发复盘时,Agent 必须执行:

  1. 扫描上下文:找出用户不满意的点(报错、风格不对、参数错误)或满意的点(特定 Prompt 效果好)。
  2. 定位 Skill:确定是哪个 Skill 需要进化(例如 yt-dlpbaoyu-comic)。
  3. 生成 JSON:在内存中构建如下 JSON 结构:
    {
      "preferences": ["用户希望下载默认静音"],
      "fixes": ["Windows 下 ffmpeg 路径需转义"],
      "custom_prompts": "在执行前总是先打印预估耗时"
    }
    

2. 经验持久化 (Persist)

Agent 调用 scripts/merge_evolution.py,将上述 JSON 增量写入目标 Skill 的 evolution.json 文件中。

  • 命令: python scripts/merge_evolution.py <skill_path> <json_string>

3. 文档缝合 (Stitch)

Agent 调用 scripts/smart_stitch.py,将 evolution.json 的内容转化为 Markdown 并追加到 SKILL.md 末尾。

  • 命令: python scripts/smart_stitch.py <skill_path>

4. 跨版本对齐 (Align)

skill-manager 更新了某个 Skill 后,Agent 应主动运行 smart_stitch.py,将之前保存的经验“重新缝合”到新版文档中。

核心脚本

  • scripts/merge_evolution.py: 增量合并工具。负责读取旧 JSON,去重合并新 List,保存。
  • scripts/smart_stitch.py: 文档生成工具。负责读取 JSON,在 SKILL.md 末尾生成或更新 ## User-Learned Best Practices & Constraints 章节。
  • scripts/align_all.py: 全量对齐工具。一键遍历所有 Skill 文件夹,将存在的 evolution.json 经验重新缝合回对应的 SKILL.md。常用于 skill-manager 批量更新后的经验还原。

最佳实践

  • 不要直接修改 SKILL.md 的正文:除非是明显的拼写错误。所有的经验修正应通过 evolution.json 通道进行,这样可以保证在 Skill 升级时经验不丢失。
  • 多 Skill 协同:如果一次对话涉及多个 Skill,请依次为每个 Skill 执行上述流程。

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