claude code for technical writers

by Ray Svitla

technical writers have a secret that developers don’t want to hear: most developer-written documentation is bad. not bad because developers can’t write — many can — but bad because documentation is maintenance work that competes with feature work, and features always win.

Claude Code shifts this equation. not by making documentation automatic (it can’t), but by making the boring parts fast enough that the interesting parts get attention.

README generation that doesn’t suck

the default Claude approach to README writing is terrible. ask it to “write a README for this project” and you get the template every GitHub repo has: project name, installation, usage, contributing, license. structurally correct, informationally useless.

the workflow that produces good READMEs:

1. let Claude read the entire codebase first. not a summary — the actual code
2. ask it to identify what the project does differently from alternatives
3. ask for the README structure, review it, adjust
4. have Claude write each section with code-aware examples

step 2 is the key. a README that starts with “this is a React component library” describes 10,000 repos. a README that starts with “this is a React component library where components auto-generate their own accessibility tests” describes one. Claude can find that differentiator by reading the code, but you have to ask for it.

API documentation

this is Claude Code’s strongest documentation use case by a wide margin.

point Claude at your API routes. it reads the handlers, middleware, validation schemas, database queries, and response types. from this, it generates endpoint documentation that includes:

→ actual request/response schemas (from your code, not your memory) → authentication requirements (from your middleware chain) → error responses (from your error handlers, not guesses) → edge cases (from your validation rules)

the accuracy is high because Claude reads the source of truth — the code — instead of relying on a human to remember what they changed three sprints ago.

pair this with the Playwright MCP for extra power: Claude can actually call your API endpoints, observe real responses, and document what happens rather than what should happen. the gap between those two is your documentation debt.

docs maintenance — the real problem

writing docs is a solved problem. keeping docs accurate is the actual crisis. every codebase over two years old has documentation that lies. confidently. with code examples that no longer compile.

Claude Code’s value for maintenance:

"read the docs in /docs and the source code in /src. 
find every place where the docs describe behavior that 
doesn't match the current code. list them with the 
specific discrepancy."

this audit takes Claude ten minutes and a human ten hours. the output isn’t perfect — Claude sometimes flags intentional differences or planned features documented early — but it catches the dangerous lies. the function signature that changed. the config option that was renamed. the endpoint that moved.

run this monthly. seriously. automate it with a cron job or a CI step. stale docs are worse than no docs because people trust them.

the danger zone

here’s where technical writers need to be cautious: Claude Code produces text that looks like good documentation. grammatically correct, well-structured, appropriately detailed. but “looks correct” and “is correct” diverge in technical writing more than anywhere else.

Claude will confidently document a function parameter that was removed two commits ago if it’s still referenced in a comment somewhere. it will describe a default value from an old version of a config file. it will invent plausible-sounding behavior for edge cases it can’t verify.

the rule: Claude drafts, humans verify. every piece of documentation Claude generates should be reviewed against actual behavior. run the code examples. call the endpoints. check the config values. the time savings from Claude generating the draft is real; spending some of it on verification is mandatory.

the workflow that works

for a documentation sprint, this is the sequence that produces the best output:

1. audit — Claude scans existing docs against code, lists gaps and lies
2. outline — Claude proposes new doc structure based on actual codebase
3. draft — Claude writes each section, pulling real examples from code
4. verify — human runs every code example and checks every claim
5. voice — human rewrites anything that sounds like Claude instead of like your team

step 5 matters more than you think. documentation has a voice. if half your docs sound like a helpful robot and half sound like your senior engineer, the inconsistency is jarring. either let Claude write everything (and edit for voice) or write the important parts yourself and let Claude handle the reference material.

tools that pair well

→ Playwright MCP — test API docs by actually calling endpoints → GitHub Actions — automated docs freshness checks in CI → a good linter for your doc format (markdownlint, vale) — Claude respects linter configs

what’s the documentation debt you’ve been ignoring the longest?

→ best skills for writers — skill recommendations → ai documentation workflow — dedicated skills → context engineering — feeding Claude the right context

Ray Svitla stay evolving