원료를 회전시키는 대리인 기술 - 기사, 회담, 기구, 최근 AI 일, 또는 단지 아이디어 - 전략적, 상호 작용하는 기술로. Bottom-up 종합, 콘텐츠 재포장.

무엇 그것

Skill-distillery는 기술을 만드는 기술입니다. 그것은 4개의 입장 점에서 작동합니다:

소스 재료 (/skill-distillery https://example.com/article) - URL, 파일, 또는 붙여진 콘텐츠를 제공합니다. 그것은 소스를 읽고, 원리와 정신 모델 바닥 업을 추출, 다음 협업으로 기술 아키텍처를 디자인.

**(/skill-distillery) - 원하는 것을 설명합니다. 설명이 상세한 경우, 직접 접근을 제안합니다. 그것이 vague라면 아이디어가 명확할 때까지 뇌가됩니다.

** 최근 작업 ** (/skill-distillery capture) - AI와 무언가를하고 프로세스를 저장하고 싶습니까? 반복 가능한 워크플로우, 결정점 및 gotchas를 추출하여 재사용 가능한 기술로 패키지합니다.

** 기존 기술** (`/skill-distillery 감사 ~/.

Skill Distillery

An agent skill that turns raw material — articles, talks, frameworks, recent AI work, or just an idea — into strategic, interactive skills. Bottom-up synthesis, not content reformatting.

What it does

Skill-distillery is a skill that creates skills. It works from four entry points:

From source material (/skill-distillery https://example.com/article) — Give it a URL, file, or pasted content. It reads the source, extracts principles and mental models bottom-up, then collaboratively designs the skill architecture with you.

From a description (/skill-distillery) — Describe what you want. If your description is detailed, it proposes an approach directly. If it’s vague, it brainstorms with you until the idea is clear.

From recent work (/skill-distillery capture) — Just did something with AI and want to save the process? It extracts the repeatable workflow, decision points, and gotchas, then packages them as a reusable skill.

Audit an existing skill (/skill-distillery audit ~/.claude/skills/my-skill) — Runs any skill through a seven-lens evaluation framework: rigor and evals, gotchas, synthesis quality, architecture, interactive design, spec compliance, and cross-agent compatibility. Produces a rated assessment with prioritized improvements.

The approach

Most skill creators assume you already know what you want to build. Skill-distillery starts earlier — from raw material — and works bottom-up.

A 5,000-word article doesn’t become a skill by restructuring paragraphs into SKILL.md format. It becomes a skill when you extract the 5 principles that make the approach work, the mental model that organizes the domain, and the decision heuristics someone needs while doing the work. Then you design an interactive architecture around those extracted elements.

The workflow is collaborative: extract → validate → choose a rigor lane → plan evals → propose architecture → build. Every phase has a checkpoint where you confirm before proceeding. The skill suggests interactive patterns from proven skills (discovery phases, mode detection, conditional loading, wait gates) as opinionated defaults you can override.

Skill-distillery now right-sizes the output for three lanes:

• Quick Personal — Lean SKILL.md, 1-3 smoke prompts, no README or publication prep by default
• Team Internal — Shared workflow with enough evals and documentation for safe reuse
• Public Polished — README, eval pack, fresh-agent test, and compatibility review

Best experience on Claude Code

Skill-distillery works with any agent that supports skills, but it’s designed to shine on Claude Code thanks to:

• AskUserQuestion — Tappable multiple-choice options for strategy decisions
• Parallel research agents — Spawns Sonnet agents for fast, scoped research when needed
• Agent tool — Launches specialized subagents for deep research