What problem does it solve? Turning long-form knowledge sources like blog posts, GitHub repos, papers, and video transcripts into reusable agent skills is hard: raw summarization produces bloated, motivational content that agents cannot act on. This Skill provides a disciplined distillation process that extracts only transferable, decision-relevant knowledge. ## Core Features & Use Cases - Source Absorption and Extraction: Reads full sources (articles, repos, docs, papers, transcripts) and separates actionable rules, patterns, and anti-patterns from motivation, history, and persuasion. - Skill Shape Decisions: Guides whether a source becomes a single SKILL.md, a SKILL.md with references/, or multiple cross-referencing skills, using an explicit decision heuristic. - Ecosystem Translation: Rewrites code examples and idioms into the user's target language (e.g., TypeScript/Bun) so output is copy-pasteable. - Use Case: You find a 5,000-word blog post on type-driven design. Use this Skill to distill it into a ~200-line skill with practical rules, TypeScript examples, anti-patterns, and a code review checklist. ## Quick Start Distill this article into a reusable agent skill with concrete rules and TypeScript examples.
