Docs and code search

Most developer time goes into reading code, not writing it. The tools in this category help with that reading. Sourcegraph searches across every repository and code host a company has, which makes it practical to find all callers of a function or every place a library is used before changing it. Swimm keeps documentation for internal code next to the code itself and flags when the code it describes changes.

For docs that other people read, platforms such as Mintlify, ReadMe and GitBook publish developer documentation and API references, and add AI search that answers a reader's question from the published pages. That helps users find answers, but only if the docs are correct to begin with, so the writing still matters more than the search box.

AI makes a few new jobs possible here: drafting first versions of docs from code, explaining an unfamiliar module in plain words, and answering questions about how a system works. Treat those outputs as drafts. A confident explanation of the wrong code path is worse than none, so check generated docs against the code before publishing them.

When choosing, look at where your docs live today, whether the tool syncs with Git, who can edit, and how it handles private repositories and internal docs. For code search, check which code hosts it connects to and whether it can run on your own infrastructure.