Project
Build a Documentation Website with AI
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.
AI Code Documentation Workflow
Generate documentation that matches the code instead of drifting from it — have AI explain what the code really does, write it up as structured docs, then validate the format holds.
The problem
Generated docs have a credibility problem: the model writes confident documentation for what it assumes the code does, and the gap between that and reality is where docs go to die. Documentation is only worth having if it matches the code — and stays matching. The reliable approach grounds the writing in an actual explanation of the code first, structures it as real docs rather than prose, and checks the output format so it slots into your docs site instead of needing a cleanup pass.
Recommended workflow
Each step uses an existing NewPrompt tool, pre-filled by a matching resource. Open the resource to read it, or jump straight into the tool with the inputs ready.
-
Explain what the code really does
Before documenting anything, get a grounded explanation of the code's actual behavior — inputs, outputs, side effects — so the docs describe reality, not an assumption.
Outcome An accurate read of the code to document from. -
Write it up as structured docs
Turn the explanation into proper documentation — overview, usage, parameters, examples — in a consistent markdown structure, not a wall of prose.
Outcome Structured docs that match the code's behavior. -
Validate the format holds
Check the markdown structure — headings, code blocks, sections — so the output drops into your docs without a manual fixup.
Outcome Docs that are structurally valid and ready to publish.
Expected outcome
Documentation that reflects what the code actually does and lands in a clean, consistent structure — ready to publish instead of needing a rewrite, and grounded enough to trust.
Best for
- Documenting code that has little or none
- Writing a README or API docs from existing code
- Keeping docs structurally consistent
Not for
- Explaining code to yourself — the Code Explanation Prompt alone is enough
- Getting up to speed on a codebase — use the AI Codebase Onboarding Workflow
FAQ
AI code documentation workflow vs the Code Explanation Prompt
The Code Explanation Prompt is only step one here — it reads what the code does. This workflow takes that explanation and turns it into published documentation: structured markdown with overview, usage, and parameters, then validates the format. Explanation is a read; this is a deliverable.
What does the AI code documentation workflow produce?
Structured markdown documentation — overview, usage, parameters, and examples — that matches what the code actually does, with the format validated so it drops into your docs site cleanly. You get publish-ready docs rather than prose, but you run the prompts in your own AI tool and review the result before shipping.
How to run the AI code documentation workflow
Work the three steps in order: paste your code into the Code Explanation Prompt to get a grounded read, feed that explanation into the Markdown Output Builder to draft structured docs, then run the AI Output Validator on the markdown. NewPrompt supplies each prompt; you run them in your own AI tool.
What if the AI documentation describes the code wrong?
Inaccurate docs usually mean step one was thin — the explanation missed a side effect or an edge case the model then wrote around. Re-run the Code Explanation Prompt with the specific function or input in focus before regenerating docs. The workflow grounds the writing, but you verify the claims against the real code.
Why explain before documenting?
Because documentation written from assumptions documents the assumptions. Grounding the docs in an actual explanation of the code is what keeps them from confidently describing behavior the code doesn't have.
Does it keep my code private?
Yes. Every tool runs in your browser and only generates prompts; you run them against your own AI. Nothing is uploaded.
Part of these projects
Complete build journeys that include this workflow as a stage.
Guides for this workflow
Guide
How to Write API Documentation With AI From Your Code
An endpoint exists but its docs don't, so "document this API" from code alone invents parameters, status codes, and an auth flow that were never real. Here's how to write API documentation with AI from the facts you provide, with unknowns flagged and checked against the real API.
Guide
How to Write a README With AI From Your Project Facts
Your README works perfectly on the one machine where the tool was already installed. Everyone else hits a missing prerequisite in the first ninety seconds. Here's how to build a README from your real setup facts — and the clean-machine run that decides whether any of it is true.
Related workflows
Workflow
AI Codebase Onboarding Workflow
Get up to speed on an unfamiliar codebase in an afternoon — ground the AI in the project, have it explain the hard parts, and keep what you learn.
Workflow
AI Project Architecture Workflow
Design a system's architecture on its real trade-offs instead of a confident diagram — put the model in an architect's seat, work the decisions one at a time, and write down the why.
Workflow
AI Meeting Notes Workflow
Turn a meeting transcript into notes people actually use — a faithful summary, the action items pulled out and assigned, and a clean shareable format.