AI coding agents have gotten very good at writing code.
But APIs are still a surprisingly easy place for them to make mistakes.
The problem isn't always that the model doesn't know the API.
Sometimes the documentation is:
- for a different version
- spread across multiple pages
- buried inside a traditional documentation site
- missing from the model's context
- inconsistent with examples found elsewhere
- full of deprecated endpoints
That's what led me to build DocOrbit.
DocOrbit is an open-source documentation intelligence layer for coding agents.
Instead of treating documentation as a giant block of text, the goal is to turn it into structured, version-aware evidence.
The pipeline looks roughly like:
Documentation discovery -> Documentation graph -> Project dependency detection -> Version resolution -> Task-specific retrieval -> API intelligence -> Implementation context -> Code/API verification
One part I'm particularly interested in is verification.
If an agent generates code using the wrong endpoint, wrong HTTP method, missing required parameters, or a deprecated API, DocOrbit can compare the implementation against the documented contract and report the result.
The project is still evolving, but the goal is simple:
Don't just give coding agents documentation. Give them the right documentation, and check whether their implementation agrees with it.
GitHub: https://github.com/HakashiKatake/docorbit
I'd love feedback from people building coding agents, MCP servers, developer tools, or documentation infrastructure.
Top comments (1)
The version-mismatch failure is the one that burns the most time because the agent looks confident and the code looks right - it is right, for a version you do not run. "Documentation exists" and "the model is grounded on the documentation that matters" are completely different states, and scattered docs make the second one accidental. The fix pattern that works for me is pinning the exact spec version into context rather than pointing at a docs site: the model will happily average five versions of an API into one fluent, wrong call.