How to document a codebase with AI: a step-by-step guide

By the end of this guide you will have documentation for a real codebase: a README that explains what the project is and how to run it, reference docs for the code or API, and a plan for keeping them current. The job is done by an AI documentation tool that reads your repository (or the code you paste), drafts the pages, and leaves you to correct and publish them.

If you want to document a codebase with AI, the main choices are whether you need a quick README, generated code and API docs, or a hosted documentation site that updates as the code changes. This guide covers each and compares seven tools from our Coding category.

Key takeaways

• Decide who the docs are for, point a tool at the repository, generate a first draft of each page type, then check every instruction and example against the real code.
• The main decision is the output: a single README, generated code and API docs, or a published documentation site with an assistant for readers.
• Free options exist but are narrow: ReadMeAI is presented as free, Mintlify's Starter plan is free for up to 5 editor seats, and Documentation.AI has a Starter plan at $0.
• AI documentation can describe code that does not behave that way. A developer who knows the project must verify install steps, examples and anything about security.

What you need before you start

• A repository you can share with the tool. Check your company policy before you connect private code.
• A target reader. New contributors, users of your API, or colleagues taking over the project need different docs.
• A list of page types. For example: README, setup guide, architecture overview, API reference and changelog.
• A clean environment. Somewhere you can follow the generated install steps from scratch.
• Time. A first set of drafts takes under an hour; reviewing them takes longer.
• Difficulty. Easy for a README, moderate for a documentation site connected to your repository.
• Access. Permission to connect the repository host, and to commit documentation files.

Which kind of AI tool fits this job

Choose by the output you need and where the docs will live.

A quick README. ReadMeAI takes a GitHub repository URL, detects the stack from files such as package.json, requirements.txt and go.mod, and produces markdown with install steps, usage examples and a contributing guide. Its listing says the output should be checked against the project. ZZZ Code AI is a set of browser tools that includes Code Documentation, Code Explainer and Code Review, useful for single files you paste in.

Generated code docs and API references. DocuWriter.ai connects to GitHub, GitLab, Bitbucket or Azure DevOps repositories and drafts code documentation, API docs, a README and UML diagrams. Its Autopilot agent applies updates when code changes.

A published documentation site. Mintlify hosts developer docs and API references stored as Markdown or MDX in your own Git repository, with an API playground and custom domains. Documentation.AI has a Documentation Agent that drafts and edits pages as commits you review, and publishes sites with an assistant for readers.

Documentation inside your coding assistant. GitHub Copilot lists generating tests and documentation among its use cases, in the editor. Qoder is a coding platform whose paid plans add Repo Wiki, which generates structured documentation for a project.

Step 1: Decide what to document and for whom

Good documentation starts with a reader, not a tool.

1. Name the main reader: a new teammate, an outside contributor, or a user of your API.
2. List the questions that reader asks first, such as "how do I run this?" and "where does the data come from?".
3. Pick the page types that answer them, and put them in priority order.
4. Note what should not be documented publicly, such as internal endpoints or credentials.

Check it worked by having a one-page outline that a teammate agrees covers the first questions.

Step 2: Tidy the code the tool will read

Tools learn from what is in the repository, so help them.

1. Make sure the project builds and the tests run from a clean checkout.
2. Add or fix names that mislead, since the tool will repeat them.
3. Remove dead code, stale scripts and secrets.
4. Keep any existing notes or comments that explain why, not only what.

Check it worked by cloning the repository to a new folder and running the setup yourself.

Step 3: Choose a tool and connect the code

You end this step with a tool picked and the code available to it.

1. For a README only, a free web tool may be enough.
2. For code and API docs, connect the repository host to a tool such as DocuWriter.ai, or use your editor assistant.
3. For a published site, check how the platform stores pages. Mintlify and Documentation.AI both work with Markdown and MDX in your own repository.
4. Look at the plan limits in the comparison table below. Several tools meter AI use in credits.

Check it worked by seeing your repository listed in the tool, or your first request returning something about the right project.

Step 4: Generate a first draft of each page type

Work one page type at a time.

1. Start with the README: what the project does, how to install it, a minimal usage example and how to contribute.
2. Generate reference docs for modules, functions or endpoints. Ask for parameters, return values and example calls.
3. Ask for an architecture overview, and a diagram if the tool offers one. DocuWriter.ai lists UML diagrams.
4. Keep every draft in a branch so nothing is published before review.

Check it worked by having a draft for each page type in your outline.

Step 5: Verify every instruction and example

AI documentation can sound right and be wrong.

1. Follow the install steps exactly as written, on a clean machine or container.
2. Run every code example and compare the output with what the docs claim.
3. Check names of functions, flags and environment variables against the source.
4. Remove claims you cannot verify, such as performance statements or security guarantees.
5. Have the author of each module read the part that describes it.

Check it worked by completing the setup and one real task by following the docs and nothing else.

Step 6: Edit for clarity and add what the code cannot say

The tool describes what the code does; only you know why.

1. Add the reasoning behind important decisions and the trade-offs you accepted.
2. Put the most common task first on each page, with the details below.
3. Add known limits, gotchas and troubleshooting notes from real support questions.
4. Cut filler and repeated sentences, and use the same terms the code uses.

Check it worked by asking someone new to the project to read it and report where they got stuck.

Step 7: Publish and keep it current

Documentation decays unless updating it is part of the workflow.

1. Merge the docs through a normal pull request so changes are reviewed.
2. If you use a hosted site, publish and add a custom domain where the plan allows.
3. Set up updates when code changes. DocuWriter.ai has an Autopilot agent, and Documentation.AI lists automation templates that update pages after merges or on a schedule. Review those updates as you would any other change.
4. Add a docs check to your review process, so code changes that alter behavior include doc changes.

Check it worked by changing a function, running the update, and seeing the affected page flagged or revised.

Tools for this job compared

Tool	Good fit for	Pricing	Stated limits
DocuWriter.ai	Code docs, API references and UML diagrams from connected repositories	Free trial, paid from $20/mo (checked 24 Oct 2026)	Each plan caps AI-generated pages per month, one credit per page; trial previews up to 10 AI-generated pages
Mintlify	Hosted developer docs and API references from your Git repo	Freemium, paid from $450/mo (checked 24 Oct 2026)	Starter has 5 editor seats and no AI assistant; AI features run on credits; self-hosting is Enterprise only
Documentation.AI	Docs site with a writing agent that commits for review	Freemium, paid from $55/mo (checked 24 Oct 2026)	AI features pause when credits run out; Starter includes 10,000 AI credits as a one-time amount
ReadMeAI	A first-draft README from a GitHub URL	Free	Input is a GitHub repository URL; usage limits and private repository support not stated
Qoder	Repo Wiki documentation inside a coding platform	Freemium, paid from $10/mo (checked 24 Oct 2026)	Repo Wiki is on paid plans; plan credits expire each billing period and do not roll over
GitHub Copilot	Editor assistant that also drafts docs and tests	Freemium, paid from $10/mo (checked 23 Oct 2026)	Free plan is capped at 2,000 inline suggestions per month and excludes the cloud agent and code review
ZZZ Code AI	Browser tools for explaining and documenting pasted code	Free	Input limited to 10000 characters, or 20000 for logged-in users; a daily limit per user applies

Prices and plan limits change, so confirm the current terms on each vendor's site before you subscribe.

Common mistakes to avoid

• Publishing the first draft. Generated text can describe behavior the code does not have. Fix it by following the instructions yourself and running every example.
• Documenting everything equally. A wall of pages hides the three that matter. Fix it by writing for one reader and putting their first questions first.
• Feeding secrets to the tool. Repositories sometimes contain keys, internal URLs or customer data. Fix it by removing them first and checking the vendor's data terms before you connect private code.
• Letting docs drift. Docs that are correct today go stale after the next release. Fix it by tying doc updates to pull requests, and by reviewing any automated changes.
• Leaving out the why. The tool sees code, not intent. Fix it by adding decisions, trade-offs and known limits yourself.

How we put this together

This is an evidence-based guide built from each tool's listing in our directory, which is compiled from the vendor's own site and pricing page. It is not a review based on using the tools. We don't rank tools, and nobody paid to be included. Some outbound links may be affiliate links; see our disclosure.

Frequently asked questions

Is there a free way to document a codebase with AI?

Yes, within limits. ReadMeAI is presented as a free README generator, Mintlify's Starter plan is free for up to 5 editor seats, Documentation.AI has a Starter plan at $0, and ZZZ Code AI offers free browser tools with a daily limit. Heavier use of repository-connected tools generally needs a paid plan.

Can AI write accurate documentation?

It can produce a useful draft quickly, but it can state things that are not true of your code. Follow the instructions, run the examples and have a developer who knows the module review the text before it is published.

Is it safe to connect a private repository?

Check each vendor first. DocuWriter.ai says it does not store your code or use it for model training, but that is the vendor's own statement. Read the data terms for your plan and your company's policy before connecting private code.

Can the documentation update itself when code changes?

Some tools offer it. DocuWriter.ai has an Autopilot agent that applies updates when code changes, and Documentation.AI lists automation templates that update docs on merges or on a schedule. Review those updates like any other change.

How long does it take?

It depends on the project. ReadMeAI says its README generation takes under ten seconds, but none of these listings gives a time for a full set of docs. Verifying the steps, adding context and publishing take longer, and the time grows with the size of the project.

Compare more options in our Coding category. To tidy the code you are documenting, see how to refactor legacy code with AI.