docvet 1.3.0

Comprehensive docstring quality vetting for Python projects

docvet

Better docstrings, better AI.

ruff checks how your docstrings look. interrogate checks if they exist. docvet checks if they're right. Existing tools cover presence and style — docvet delivers the layers they miss:

Layer	Check	ruff	interrogate	pydoclint	docvet
1. Presence	"Does a docstring exist?"	--	Yes	--	--
2. Style	"Is it formatted correctly?"	Yes	--	--	--
3. Completeness	"Does it have all required sections?"	--	--	Partial	Yes
4. Accuracy	"Does it match the current code?"	--	--	--	Yes
5. Rendering	"Will mkdocs render it correctly?"	--	--	--	Yes
6. Visibility	"Will mkdocs even see the file?"	--	--	--	Yes

pydoclint checks Args/Returns/Raises alignment with function signatures (structural completeness). docvet's enrichment covers that plus Yields, Receives, Warns, Attributes, Examples, typed attributes, and cross-references -- 19 rules across 4 checks. docvet also covers freshness (git diff/blame), griffe rendering compatibility, and mkdocs coverage -- territory no other tool touches.

Quickstart | GitHub Action | Pre-commit | Configuration | Docs

What It Checks

Enrichment (completeness) -- 10 rules: missing-raises missing-yields missing-receives missing-warns missing-other-parameters missing-attributes missing-typed-attributes missing-examples missing-cross-references prefer-fenced-code-blocks

Freshness (accuracy) -- 5 rules: stale-signature stale-body stale-import stale-drift stale-age

Griffe (rendering) -- 3 rules: griffe-unknown-param griffe-missing-type griffe-format-warning

Coverage (visibility) -- 1 rule: missing-init

Quickstart

pip install docvet && docvet check --all

For optional griffe rendering checks:

pip install docvet[griffe]

Example output:

src/mypackage/utils.py:42: missing-raises Function 'parse_config' raises ValueError but has no Raises section
src/mypackage/models.py:15: stale-signature Function 'process' signature changed but docstring not updated
src/mypackage/api.py:1: missing-init Package directory missing __init__.py (invisible to mkdocs)

Configuration

Configure via [tool.docvet] in your pyproject.toml. All checks run and print findings. Checks listed in fail-on cause a non-zero exit code; unlisted checks are treated as warnings.

[tool.docvet]
exclude = ["tests", "scripts"]
fail-on = ["griffe", "coverage"]

[tool.docvet.freshness]
drift-threshold = 30
age-threshold = 90

Pre-commit

Add to your .pre-commit-config.yaml:

repos:
  - repo: https://github.com/Alberto-Codes/docvet
    rev: v1.2.0
    hooks:
      - id: docvet

For griffe rendering checks, add the optional dependency:

repos:
  - repo: https://github.com/Alberto-Codes/docvet
    rev: v1.2.0
    hooks:
      - id: docvet
        additional_dependencies: [griffe]

GitHub Action

Add docvet to your GitHub Actions workflow:

- uses: Alberto-Codes/docvet@v1

With version pinning and custom arguments:

- uses: Alberto-Codes/docvet@v1
  with:
    version: '1.2.0'
    args: 'check --all'

For griffe rendering checks, install griffe before running docvet:

- uses: actions/setup-python@v5
  with:
    python-version: '3.12'
- run: pip install griffe
- uses: Alberto-Codes/docvet@v1
  with:
    args: 'check --all'

Better Docstrings, Better AI

AI coding agents rely on docstrings as context when generating and modifying code. Research shows stale or incorrect documentation is actively harmful -- worse than no docs at all:

• Incorrect docs degrade LLM task success by 22.6 percentage points
• Comment density improves code generation by 40-54%
• Misleading comments reduce LLM fault localization accuracy to 24.55%
• Performance drops substantially without docstrings

As the 2025 DORA report puts it: "AI doesn't fix a team; it amplifies what's already there." The only signal correlating with AI productivity is code quality.

docvet's freshness checking catches the accuracy gap that stale docs create, and its enrichment rules ensure the docstring sections that agents use as context are complete. Run docvet check in your CI, pre-commit hooks, or agent toolchain.

Badge

Add a badge to your project to show your docs are vetted:

[![docs vetted | docvet](https://img.shields.io/badge/docs%20vetted-docvet-purple)](https://github.com/Alberto-Codes/docvet)

Used By

Are you using docvet? Open a pull request to add your project here.

License

MIT -- see LICENSE for details.