ai-doc-writing

AI-optimized documentation converts verbose prose into structured data by enforcing strict heading hierarchy, replacing narrative text with YAML/code blocks, and removing meta-commentary. This produces clean, parseable content that AI systems consume efficiently without fluff or ambiguity.

Fluff includes meta-commentary, conversational language, inconsistent heading structure, and prose that could be replaced by imperative steps or structured data. The fluff detector identifies these patterns so you can refactor toward completeness and efficiency—the core principles for AI-context docs.

Yes. The Skill covers refactoring API references, setup guides, architecture references, workflow guides, and configuration specs. Feed Markdown documents to the workflow, request restructure into YAML blocks with concise imperative steps, and validate examples against the style guide.

Human-focused docs prioritize narrative flow and explanation; AI-optimized docs prioritize structure, completeness, and zero fluff. AI-context documentation uses strict heading hierarchy, structured data blocks over prose, and removes conversational language so AI systems extract intent and requirements without parsing ambiguity.

Check for three criteria: completeness (all essential details present), efficiency (no redundant or conversational text), and zero fluff (no meta-commentary or heading hierarchy violations). The Skill provides a fluff detector and style guide to validate that your refactored docs meet these standards.