dbt-coverage

What it is and what it does

dbt-coverage is a CLI tool that measures how thoroughly your dbt project is documented and tested. It reads the manifest.json and catalog.json files that dbt generates, then reports coverage percentages for each model and the project overall. You run it after dbt docs generate to get a snapshot of which models lack documentation or test coverage.

The tool is designed to integrate into CI/CD pipelines and help teams enforce documentation and testing standards. It supports filtering by model path, outputting results to JSON files, and formatting reports as Markdown tables. With only typer as a runtime dependency and roughly 480 lines of code, it is lightweight and straightforward to audit.

Use it for:

• Enforce minimum documentation coverage in CI/CD by failing builds when docs fall below a threshold
• Audit a newly inherited dbt project to quickly identify which models lack documentation or tests
• Track documentation and test coverage trends over time by storing JSON reports in version control
• Generate Markdown coverage reports for team dashboards or pull request comments
• Filter coverage reports to specific model directories to focus on particular layers of your dbt DAG

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Measures documentation and test coverage of dbt projects by analyzing manifest and catalog files, reporting per-model coverage percentages and totals via CLI.

Yes. dbt-coverage fills a clear gap in dbt project quality assurance with minimal dependencies, active maintenance, and no known vulnerabilities. Install it if you want to measure and enforce documentation and test coverage in your dbt projects; the zero-config design and low friction make it a straightforward addition to any dbt workflow.

Install

dbt-coverage on PyPI

pip install dbt-coverage

uv add dbt-coverage

poetry add dbt-coverage

Installing dbt-coverage

Before you install

Low friction install with only typer as a runtime dependency. Actively maintained as of 2026-04-29 with 241 repository stars.

License in practice

MIT license permits unrestricted use, modification, and distribution with minimal legal friction.

Quickstart

pip install dbt-coverage

cd your_dbt_project
dbt run && dbt docs generate
dbt-coverage compute doc --cov-report coverage.json

# Output shows per-model and total documentation coverage percentages

Requires a dbt project with target/manifest.json and target/catalog.json files, which are generated by running 'dbt docs generate' in your dbt project directory.

Verify before relying

• Whether dbt itself is assumed to be pre-installed or if dbt-coverage handles dbt installation
• Performance characteristics on large dbt projects with hundreds or thousands of models
• Exact dbt version compatibility beyond the 'optimized for dbt 1.0' statement in the description

Package facts

Evidence: dbt_coverage-0.4.2-py3-none-any.whl

Tags

More Quality Assurance packages

Further reading