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Found 4,092 Skills
Unified learning-and-memory system: confidence-scored instincts (observe-hypothesize-confirm, stored in .claude/instincts.md), user corrections captured as permanent rules in MEMORY.md, and organic discoveries logged to .claude/learning-log.md. Includes status, export, and import modes. Load this skill when you notice a recurring pattern, a user corrects your output, or you discover something non-obvious. Triggers: "show instincts", "what have you learned", "list instincts", "export instincts", "share instincts", "import instincts", "load instincts from", "learn this", "I think they always", "notice a pattern", "instinct", "hypothesis", "confidence", "learn from mistakes", "remember this", "don't do that again", "log this", "document this finding", "gotcha", "what did we learn", "learnings", "discoveries", or at session start (to load existing knowledge).
Use when an agent is asked "what did I (or my team) work on yesterday / this week / today" across provider data in a relayfile mount (Linear, GitHub, Notion, Slack, Confluence, Jira, etc.). Tells the agent to consult the pre-computed `digests/yesterday.md` (and sibling digest files) at the workspace root BEFORE doing manual exploration with `ls`/`grep`/`find`. The digest is deterministic, exhaustive over the window, and costs one file read instead of dozens of provider queries.
Search for Agent Skills in SkillsMP (an index of 1.6M+ public SKILL.md files, covering Claude Code / Codex / ChatGPT), filter by keywords, categories, occupations, and languages, and specifically discover those underrated Skills that are "well-written but unknown". Use this when users say phrases like "find a skill", "is there an existing skill?", "search for a skill", "skillsmp", "skills market", "agent skill search", "find a skill", "search skills", "discover skills". It is also used to identify existing Skills in a certain field and avoid reinventing the wheel.
Grades a repo's agent skills by scoring agent conversations against efficiency and code-quality rubrics, then drafts concrete skill edits and a shareable report. Use when the user wants their agent setup graded from real conversation history, or asks which of their installed skills are actually working.
Use when renaming a spec plan and updating all references. Triggers on: "rename plan", "change plan name", "plan name is wrong", "update plan name", "fix plan name", "spec rename". Proactively suggest when a plan name is a typo or no longer reflects scope.
Baidu Web Search skill for real-time Chinese web information retrieval. Breaks through static knowledge base limitations to get the latest news and information. Use when user needs to search the Chinese web for current information.
Create New Skill - scaffolds a skill definition following Claude Code conventions and this repository's patterns. Use when adding a new skill.
The always-on protocol for the loam skill namespace. Use at session start and whenever a loam task appears. Routes goals and other loam work, explains the memory model (memory = umbrella; wiki, guidance, and checkpoints are substrates), and lists cross-cutting rules. This is a routing/meta skill — delegate to a specific loam skill rather than performing work itself.
Helps an agent inspect a repository and produce C4 architecture documentation. Use this when reverse engineering a codebase, documenting system context, containers, components, or clarifying architecture from code and infrastructure.
Create or revise agent skills. Use when adding a new skill file, renaming a skill, simplifying an existing skill, improving trigger descriptions, or deciding what belongs in a skill versus references, scripts, assets, or ordinary docs.
Applies this repository's skill-authoring standard as a procedure. Use for any change to, or judgment about, a file under skills/** — a SKILL.md, a reference, a persona prompt, a bundled script's instructions: creating a skill, editing one, reviewing a skill change, or acting on review feedback (human or bot) about one. Not for src/, tests/, or scripts/ code.
[user/auto] 하나의 observed 또는 measured Agent Skill anomaly를 fresh context에서 재현·격리한 뒤, 검증된 skill objective를 tk-learn으로 라우팅한다. selection, instruction, output, host, eval, stability 또는 resource incident에 사용한다. ordinary code bug, static audit, new skill creation 또는 symptom-free optimization에는 사용하지 않는다.