By UniM0cha
복잡한 작업 후 재사용 가능한 기법을 SKILL.md로 자동 증류하고 기존 스킬을 스스로 개선하는 자기개선 루프 (Nous Research Hermes Agent 방식의 Claude Code 이식)
학습 스킬 하나를 수동으로 아카이브한다 (선택적으로 umbrella 병합 기록)
학습된 스킬 라이브러리(~/.claude/skills)를 정리한다 — umbrella 통합, 오래된 스킬 아카이브
큐레이터 변경 전 스냅샷으로 학습 스킬 라이브러리 전체를 되돌린다 (usage 메타 포함, 롤백 자체도 언두 가능)
자기개선 루프 상태를 조회한다 — 학습 스킬별 사용 빈도·상태·마지막 큐레이션
방금 작업에서 재사용 가능한 기법을 학습 스킬(~/.claude/skills)로 증류한다 (수동 트리거)
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
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Hermes Agent-style self-improvement for Claude Code, Claude Cowork, Codex, and ChatGPT work.
It turns hard-won workflow lessons into reusable
SKILL.mdfiles, validates skill edits, curates stale knowledge, and (since v0.9.0) lets a team share learned skills through a git repo — without ever overwriting anyone's personal customizations.
Claude Code already has hooks, subagents, slash commands, and skills. This plugin wires those primitives into a closed learning loop inspired by Nous Research Hermes Agent:
complex task → distill what worked → save/patch a skill → rediscover next session
One repo, four ports of the same closed learning loop:
| Plugin | Environment |
|---|---|
claude-code-self-improving-skills | Claude Code CLI (this README's main subject) |
claude-cowork-self-improving-skills | Claude Cowork (cloud container) — persists skills via claude.ai '스킬 저장' |
chatgpt-codex-self-improving-skills | OpenAI Codex CLI (hooks + MCP skill manager) |
chatgpt-work-self-improving-skills | ChatGPT desktop Work (skills-only package, under chatgpt-work/) |
Install one per environment — do not install two variants into the same environment (duplicate hooks/nudges).
Most coding agents can solve a hard problem once. Fewer can reliably remember the reusable part of that work and apply it later.
Hermes Agent has first-class procedural memory through skills and a curator loop. This project ports that idea into Claude Code as a plugin:
~/.claude/skills/<name>/SKILL.md through a dedicated subagent.Stop hook blocks once per segment of work when enough tool calls and file edits accumulated since the last distillation. A declined nudge stays declined; it only re-fires after another threshold of new work. The nudge includes the transcript path so the background distiller can read what actually happened.SKILL.md. Non-blocking quality advisories (e.g. over-long descriptions that cost context in every session).~/.claude/self-improve/skill_usage.json. Patch counting runs in the PostToolUse hook so edits made by background subagents are captured too, and bulk reads during curation never reset a skill's idle clock.use_count >= 3) age at half speed. The LLM curation pass (/curate-skills) is an umbrella-building consolidation modeled on Hermes' curator prompt — plan first, apply only after approval./distill-skill, /curate-skills, /curator-status, /prune-skills, /archive-skill, /pin-skill, /restore-skill, /share-skill, /sync-team-skills, /propose-plugin-improvement.Point the plugin at your team's (usually private) skills repo — nothing is hardcoded:
// ~/.claude/self-improve/team_config.json
{
"repo": "your-org/your-team-skills",
"subdir": "skills"
}
/share-skill <name>: the skill is scanned (secrets, local paths, injection patterns), generalized (techniques stay, personal style is stripped), shown to you as a diff, and opened as a PR against the team repo. A human merges./sync-team-skills: a fresh shallow clone, a read-only plan you confirm, then per-skill transactional apply.The origin-hash rule makes sharing safe by construction. Each installed team skill records a deterministic content hash at install time:
npx claudepluginhub unim0cha/self-improving-skills --plugin claude-code-self-improving-skillsCowork(클라우드 컨테이너) 전용 자기개선 루프 — 증류된 스킬을 SendUserFile→'스킬 저장'으로 claude.ai에 영속화하고, 콜드 컨테이너의 SessionStart×플러그인 동기화 race를 UserPromptSubmit 안내로 회피 (claude-code-self-improving-skills의 Cowork 변형)
Cowork(클라우드 컨테이너) 전용 자기개선 루프 — 증류된 스킬을 SendUserFile→'스킬 저장'으로 claude.ai에 영속화하고, 콜드 컨테이너의 SessionStart×플러그인 동기화 race를 UserPromptSubmit 안내로 회피 (claude-code-self-improving-skills의 Cowork 변형)
Agent Skills for improving SKILL.md files: mine repeated workflows from history, personalize and audit existing skills, or generalize personal skills for publication.
Curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills.
Self-Improving Agent: curate auto-memory, promote learnings to CLAUDE.md and rules, extract proven patterns into reusable skills. Provides /si:memory-review, /si:promote, /si:extract, /si:memory-status, and /si:remember slash commands.
Automatically detect workflow patterns, generate skills, and load them dynamically mid-session
Self-Evolving AI Coding Infrastructure — Generate, Curate, and Enhance Reusable Wisdom