Tools: Your AI Reads Your Docstrings. Are They Right?

The gap in your toolchain ## docvet fills that gap ## Try it ## Why this matters for AI Copilot, Claude Code, Cursor — they all read your docstrings to understand your code. When those docstrings are wrong, your AI makes confident, wrong suggestions. And wrong docs are worse than no docs. Studies show incorrect documentation drops LLM task success by 22 percentage points compared to correct docs. Your linter checks style. But who checks that the docstring is actually accurate? Existing tools cover the basics: But neither checks whether your docstring matches the code. A function that raises ValueError but doesn't document it. A parameter added last sprint but missing from the docstring. Code that changed but the docstring didn't. That's layers 3–6 of docstring quality — and nothing was checking them. docvet is a CLI tool that vets docstrings across six quality layers: Run it on your codebase. You'll probably find something. Docstrings are no longer just for humans reading your code. They're the context window for every AI tool touching your codebase. Accurate docstrings create a feedback loop: better context → better AI suggestions → better code. docvet keeps that contract honest. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse COMMAND_BLOCK: pip install docvet docvet check --all Enter fullscreen mode Exit fullscreen mode COMMAND_BLOCK: pip install docvet docvet check --all COMMAND_BLOCK: pip install docvet docvet check --all - ruff — docstring style and formatting - interrogate — docstring presence