dsh-skill-evolution
Watches agent execution traces and fires an LLM review at every successful turn end when signals trip, crystallizing reusable workflows into registered skills that improve progressively with later runs.
观察 agent 执行轨迹，在每个成功回合结束时按信号触发 LLM 评审，把值得复用的工作流结晶为已注册技能，并随后续运行持续改进。
How to install
dsh plugin add github:VanadisGithub/dsh-skill-evolution About
dsh-skill-evolution English | 中文 A **skill self-evolution plugin** for DeepSeek Harness (DSH): it watches agent execution traces and, at the end of every successful turn, fires an LLM review when signals trip — distilling workflows worth reusing into **crystallized skills** registered in the skill catalog. Later runs of the same workflow fold fresh lessons into the existing skill — skills are alive and get better with use. Highlights **Event-driven crystallization** — review fires at turn end, not on pure frequency counting; any of three signals (complex / recovered / repeated) sends the turn …
Recommendation signals
Meta
- License
- MIT
- Language
- JavaScript
- GitHub stars
- 2
- mo. downloads
- –
- Last push
- 2026-09-07
- Created
- 2026-09-01
Links
Basic safety check
- Findings
- curated 收录但无 npm 包/安装命令
- Sources
- curated:awesome-dsh-plugin.com, curated:awesome-dsh-plugin/awesome-dsh-plugin
- Topics
- agent-memory, cordis, deepseek-harness, dsh, dsh-plugin, plugin, self-evolution, skill
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