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.
Objective, Background, Findings, Recommendations, Open Questions — briefs where what was found and what to do stay clearly separated.
Research briefs lose credibility in one move: recommendations that smuggle past the findings. This setup generates briefs in five pinned sections with the type rule stated outright — separate what was found from what is recommended; different sections, different claims — plus evidence discipline: state the confidence or evidence behind each finding. Open Questions is pinned so unknowns get documented instead of papered over, and optional tables handle the comparison grids research briefs lean on.
One brief shape per program
Every study reports in the same five sections — stakeholders learn to navigate them once.
Audit the findings-recommendation seam
Each recommendation should trace to a finding above it; the structure makes orphans visible.
Respect Open Questions
A pinned unknowns section is what separates research from advocacy.
It writes a type rule directly into the DOCUMENT block — 'separate what was found from what is recommended; different sections, different claims' — and pins Findings and Recommendations as distinct '## ' headings. Findings carries what was found with evidence; Recommendations carries what to do, grounded in those findings. The generated prompt draws the seam; confirming each recommendation traces to a finding is on you.
The DOCUMENT block adds an explicit rule — 'state the confidence or evidence behind each finding' — so each item in Findings carries its basis rather than a bare assertion, calibrating how much weight a stakeholder gives each point. The Markdown Output Builder bakes this instruction into the prompt; the assistant you run it in supplies the evidence wording, and you confirm it actually holds.
Yes — the TABLE RULES permit a markdown table when content is naturally tabular, like option matrices or parameter lists, each with a header row and a separator row. But CODE RULES bar code blocks outright, and the CONSISTENCY rule says put extra material inside the closest existing section, so a comparison grid lives within Findings or Background, not as its own heading.
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.
Ask AI to analyze something and it hands back one smooth paragraph where you can't tell what you told it from what it assumed from what it's recommending. Here's how to make it split the answer into visible layers — facts, assumptions, inferences, recommendations, and what still needs checking.