Autonomously optimize a Claude Code skill or agent system by running it repeatedly, scoring outputs against evals, mutating owned artifacts (prompt, references, scripts, agent definitions), and keeping improvements. Karpathy's autoresearch methodology. Trigger when the user asks to run autoresearch, or to optimize, benchmark, or run evals on a skill or agent. Also trigger on 스킬 개선, 스킬 최적화, 스킬 벤치마크, 스킬 평가, 에이전트 개선, 에이전트 최적화.
Agentic system design blueprint generator. Interviews the user to understand a task they want to automate, then produces a comprehensive integrated design document (.md file) that serves as a concrete implementation plan for Claude Code. The design document includes task context, workflow definition with LLM vs code boundaries, and implementation spec (folder structure, agent architecture, skills/scripts list, sub-agent design). Trigger on "/blueprint", "blueprint", "에이전트 설계", "설계서 만들어", "agentic workflow design". Use this skill when the user mentions automation design, workflow planning, agent architecture, system blueprinting, or multi-step AI workflow planning.
Socratic interview skill to deepen a spec or refine an existing agent blueprint. Use when the user wants to clarify a task, stress-test design decisions, or fill gaps in a blueprint produced by /blueprint. Trigger on "/deep-dive", "deep dive", "interview me", "create a spec", "요구사항 정리", "기획서 만들어", "스펙 작성", "blueprint 심화", "설계 보강".
Autonomously optimize any Codex skill or agent system by running it repeatedly, scoring outputs against evals (binary for rules + comparative for quality), mutating any owned artifact — the skill's prompt, reference assets, and executable artifacts (scripts, agent/subagent definitions like `agents/openai.yaml`, MCP servers, hooks, harness code) — and keeping improvements. Based on Karpathy's autoresearch methodology. Use this skill whenever the user mentions optimizing a skill, improving a skill or agent, running autoresearch, making a skill or agent better, self-improving a skill, benchmarking a skill, evaluating a skill, running evals on a skill, optimizing an agent system, or any request to iteratively test and refine a skill or agent — even if they don't use the word "autoresearch" explicitly. Also trigger on 스킬 개선, 스킬 최적화, 스킬 벤치마크, 스킬 평가, 에이전트 개선, 에이전트 최적화. Outputs an improved target skill file (and any mutated executable artifacts), a results log, a changelog, and a research log of meaningful direction
Session wrap-up and fix-learning capture skill. Use when the user explicitly asks for "/reflect", "reflect", "session reflect", "end session", "세션 정리", "오늘 한 거 정리", or "마무리", or when the user clearly confirms that a concrete issue from the current coding session is fixed ("고쳐졌다", "해결됐다", "it's fixed", "working now", "that worked", "problem solved"). Explicit invocation runs Full Reflect; confident fix confirmation runs Quick Reflect.
Codex용 자동화 에이전트 시스템 설계서 생성 스킬. 사용자 인터뷰로 요구사항을 정리하고 Codex 구현 기준의 통합 설계 문서(.md)를 작성한다. Use when the user asks for "$blueprint", "blueprint", "에이전트 설계", "설계서 만들어", "agentic workflow design", or any request to plan a Codex automation or agent workflow.
A Codex skill for Socratic interviews that deepen a spec or refine an existing agent blueprint. Conducts forcing-question interviews, challenges premises, generates alternatives, and validates the final document with a document-grounded reviewer pass. Use when the user asks for "$deep-dive", "deep dive", "interview me", "create a spec", "요구사항 정리", "기획서 만들어", "스펙 작성", "blueprint 심화", or "설계 보강", or when they have a rough idea or an existing blueprint that needs structured stress-testing in Codex.
Session wrap-up and fix-learning capture skill for Codex. Use when the user explicitly asks for "$reflect", "reflect", "session reflect", "end session", "세션 정리", "오늘 한 거 정리", or "마무리", or when the user clearly confirms that a concrete issue from the current coding session is fixed ("고쳐졌다", "해결됐다", "it's fixed", "working now", "that worked", "problem solved"). Explicit invocation runs Full Reflect; confident fix confirmation runs Quick Reflect.