cratis-llm-friendly-documentation

原文涵盖的主题

• Documentation that an assistant can retrieve and cite
• Start with the existing publishing system
• Keep discovery aligned with the reader journey
• Design progressive retrieval
• Verify retrieval, not merely file existence

A giant text file is downloadable, but it is rarely the right context for one question. Help an assistant choose the relevant product, supported version and workflow, then retrieve a small, complete explanation. Keep human documentation canonical: generate alternate representations from the same source and build, not a separately authored AI manual. Inspect the source map, routes, renderer, content collection, existing indexes, page actions, and build/deploy hooks. A synchronized .mdx source can still contain imports, JSX, hidden tab alternatives, and component-only meaning; renaming or copying it to .md does not make it clean rendered Markdown. Inspect actual output before calling it LLM-friendly. A routing index and a full-text export serve different retrieval needs. Neither proves crawler adoption, answer quality, or that an entire product will fit a model's context window. Follow the documentation rule for Platform naming and product claims: route an umbrella query to the relevant component, without implying that a single-component task needs every product. A root index should expose that first useful path; product and task indexes should continue it with enough context to iden

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