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Found 13,839 Skills
Complete the incomplete behaviours in current scope — read the scoped specs, build a queue, and keep working across turns until the definition of done is satisfied. Use when the user says "run the implementation plan", "continue the plan", "finish the scoped work", "complete the incomplete behaviours", "ship B4", or names a chunk ID.
Extract a behavioral specification from a source-code bundle — a handful of files up to a whole 500+ file application. Produces reproducible, stack-neutral specs another engineer or LLM could use to rebuild the same observable behavior without reading the original source.
This skill is used when the answer requires web retrieval or independent multi-source verification, including fact-checking, technical comparison, current information, conflicting claims, important suggestions, as well as in-depth research that requires multiple rounds of deep exploration and iterative convergence.
Rebuild the human's lost context on a project from live state, in plain language: what needs them, what changed, what new words mean. Use when the human returns after a gap, says they can't follow the project anymore, asks what happened or what a term means, or before deciding what to do next when their mental model is stale. Read-only; it briefs, it does not act.
Use the Trove hosted memory graph (MCP server "trove") to recall prior work, decisions, preferences, and system knowledge before re-deriving them, and to save durable new facts back. Trigger whenever a question touches past projects, "how does my setup work", preferences, decision history, or when a session produces a decision or fact worth remembering. Routes to the trove-recall, trove-remember, trove-ingest, and trove-lint skills; the mcp__trove__* tools (remember, recall, grep, read, connect, forget) are the interface.
Execute complete FPF cycle from hypothesis generation to decision
Comprehensive multi-perspective review using specialized judges with debate and consensus building
Generate and critically evaluate grounded improvement ideas for the current project. Use when asking what to improve, requesting idea generation, exploring surprising improvements, or wanting the AI to proactively suggest strong project directions before brainstorming one in depth. Triggers on phrases like 'what should I improve', 'give me ideas', 'ideate on this project', 'surprise me with improvements', 'what would you change', or any request for AI-generated project improvement suggestions rather than refining the user's own idea.
[BETA] Execute work plans with external delegate support. Same as ce:work but includes experimental Codex delegation mode for token-conserving code implementation.
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).
Turn the current conversation into a spec (Problem, Solution, User Stories, Decisions) and publish it as a GitHub issue. Validates a feature before any code is written.
[user] 명시적인 작업 원천을 저장소 근거와 자연스러운 대화로 구체화해, 새 세션이나 더 낮은 수준 실행자가 원 대화 없이 사용할 수 있는 `.tigerkit/seed.md`를 준비합니다.