Markdown Output Prompt — Lock the Document Structure
The contract that stops AI documents from restructuring themselves: a pinned section skeleton, forced tables, and strict consistency rules.
Turn website goals, audiences, content types, and conversion paths into a sitemap and information-architecture spec: navigation, a page inventory, hierarchy, URLs, user journeys, and an internal-linking plan.
A website structured page by page becomes a maze — navigation no one can follow and pages that don't connect to a goal. This prompt builds the information architecture first: from the site's purpose, audiences, content types, and conversion paths it produces an IA specification — primary and secondary navigation, a full page inventory, the page hierarchy, URL/slug recommendations, the key user journeys, content requirements per page, an internal-linking plan, indexability notes, and the IA risks and open questions. It is a planning artifact a team builds from, not a crawl: it does not draw a visual sitemap diagram, generate an XML sitemap file, or run a technical SEO audit — it produces a sitemap-ready textual outline you can turn into either. It is for organizing a multi-page site (a company site, a docs site, or a knowledge base), distinct from structuring a single long reference document.
Start from goals, not pages
Navigation and page inventory trace to audience goals and conversion paths, so the structure serves visitors, not the org chart.
Make the hierarchy explicit
A page tree, URLs, and per-page content requirements turn a vague "site map" into something a team can build.
Connect and de-risk
An internal-linking plan ties pages to the conversion paths, and IA risks become open questions instead of post-launch surprises.
Neither — it produces a textual IA specification. A Rules line states it does "not draw a visual sitemap, generate an XML sitemap file, or claim to crawl the site." What you get is item 12, a SITEMAP-READY OUTLINE that "a developer or a diagramming tool can render." The markdown-output-builder shapes the prompt; you run it, then feed the outline into whatever tool draws or crawls.
Every page must trace to an audience goal or a content type you supplied — a Rules line bars "speculative pages." You paste the purpose, audiences, content types, and conversion paths; PAGE INVENTORY groups each page by section with a one-line purpose, and grouping follows "how visitors think, not by how the company is organized." Unresolved grouping goes into IA RISKS & OPEN QUESTIONS rather than being guessed.
It's built for multi-page sites, not a single document. The output is site-shaped — PRIMARY NAVIGATION, PAGE HIERARCHY as an indented tree, KEY USER JOURNEYS across pages, and an INTERNAL-LINKING PLAN toward the conversion paths. Those assume many pages connecting to goals. Organizing sections within one long document is a different job, which the notFor points to Structure Large Reference Documents for.
The contract that stops AI documents from restructuring themselves: a pinned section skeleton, forced tables, and strict consistency rules.
Overview, Installation, Usage, Examples, Configuration — the README skeleton with required, runnable code examples.
Overview, Authentication, Endpoints, Error Handling, Rate Limits — endpoint docs in an identical structure, with parameter tables and runnable examples forced.
Summary, Why It Matters, What Happens Next — the executive summary contract for readers who will never open the source.
Stop getting 'Sure, here is the JSON…' — the output-contract pattern that forces models to return only parseable JSON: schema, example, and a strict rule block.
The JSON won't parse and you can't see why. Deterministic cause-sniffing — trailing commas, single quotes, unclosed brackets — and the repair prompt that fixes it.
Build prompts that produce documents in a fixed structure — headings, sections, and tables.
The full path to a business website that holds together — plan the content, structure the site, design the components, write the page copy, then ship it as one coherent whole.
The full path to docs people can actually navigate — plan the doc set, structure the site, write the guides and the API reference, then ship it as a coherent documentation site.
The full path to knowledge that's findable by people and AI — plan the taxonomy, structure it for search, write the articles, tag the metadata, make it retrievable, then ship it maintainable.
Organize a site so people and crawlers find things — inventory the content, group it into a real hierarchy, design the sitemap and navigation, then document the information architecture for the build.