skills/skill-lifecycle-manager/SKILL.md
Skills 生命周期管理器 - 版本管理、依赖检查、使用统计和健康报告
npx skillsauth add OliverOuyang/shuhe-work-skills skill-lifecycle-managerInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Skills 生命周期管理器,提供版本管理、依赖检查、使用统计和健康报告功能。
# 查看所有 skills 版本
/skill-lifecycle-manager version list
# 查看特定 skill 版本信息
/skill-lifecycle-manager version info <skill-name>
# 升级版本
/skill-lifecycle-manager version bump <skill-name> <major|minor|patch>
# 检查所有依赖
/skill-lifecycle-manager deps check
# 查看特定 skill 的依赖
/skill-lifecycle-manager deps show <skill-name>
# 检测依赖冲突
/skill-lifecycle-manager deps conflicts
# 查看统计摘要
/skill-lifecycle-manager stats summary
# 查看特定 skill 统计
/skill-lifecycle-manager stats show <skill-name>
# 导出统计数据
/skill-lifecycle-manager stats export <output-file>
# 生成完整健康报告
/skill-lifecycle-manager health report
# 查看 skill 健康评分
/skill-lifecycle-manager health score <skill-name>
# 获取改进建议
/skill-lifecycle-manager health suggest
# 1. 检查所有依赖
/skill-lifecycle-manager deps check
# 2. 如果发现问题,查看详情
/skill-lifecycle-manager deps show <problematic-skill>
# 3. 生成依赖报告
/skill-lifecycle-manager deps conflicts
# 1. 查看当前版本
/skill-lifecycle-manager version info my-skill
# 2. 升级补丁版本
/skill-lifecycle-manager version bump my-skill patch
# 3. 验证版本已更新
/skill-lifecycle-manager version info my-skill
# 生成完整报告
/skill-lifecycle-manager health report
# 查看输出的 Markdown 文件
# 报告位置: data/health-report-YYYYMMDD.md
所有数据存储在 skills/skill-lifecycle-manager/data/ 目录下:
usage_stats.db - SQLite 数据库(使用统计)health-report-*.md - 健康报告(Markdown 格式)dependency-report.json - 依赖分析结果可以通过配置文件自定义行为(可选):
{
"stats_retention_days": 90,
"health_score_threshold": 70,
"auto_backup": true
}
配置文件位置:data/config.json
# 删除并重新初始化数据库
rm data/usage_stats.db
/skill-lifecycle-manager stats summary
# 清理缓存并重新扫描
/skill-lifecycle-manager version list --refresh
# 运行单元测试
cd skills/skill-lifecycle-manager
pytest tests/
# 运行特定测试
pytest tests/test_version_manager.py
# 查看覆盖率
pytest --cov=scripts tests/
/skill - 基础 skill 管理/learner - 从对话中提取新 skill/skill-auto-evolver - Skills 自动进化器tools
SQL 分段验证、自我修复、结果导出与智能分析。流程:解析SQL → Dataphin MCP 验证元数据 → 自动修复 → 分段执行验证 → 导出 CSV → 智能分析(漏斗解读、异常识别、预判用户问题)。适用场景:"跑一下这个SQL"、"验证这个查询"、"帮我执行并导出"、"分析一下结果"等。
testing
Security-first vetting for OpenClaw skills. Use before installing any skill from ClawHub, GitHub, or other sources. Checks for red flags, permission scope, and suspicious patterns.
development
A universal self-improving agent that learns from ALL skill experiences. Uses multi-memory architecture (semantic + episodic + working) to continuously evolve the codebase. Auto-triggers on skill completion/error with hooks-based self-correction.
data-ai
Standardize Jupyter notebooks (.ipynb) for interactive data analysis workflows. Enforces a mandatory cell manifest (M1-M8 + archetype chapters) with tags ([CONFIG]/[SETUP]/[FUNC]/[RUN]/[VIZ]/[EXPORT]), structured markdown sections, and output prefixes ([OK]/[WARN]/[SKIP]). Use when the user wants to standardize, clean up, or create a notebook from scratch. Two archetypes: problem-driven (question-answer analysis) and monitoring (dimension-based periodic reporting).