Test-First Workflow Uses Automated Checks to Keep AI-Generated Docs Accurate

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AI code assistants can quickly generate documentation, but the content often becomes outdated or inaccurate when code changes go unchecked. A test-first documentation workflow treats docs like code, requiring each claim to pass automated validation before it is considered complete. The approach uses Python tools such as doctest to execute inline examples and a custom AST script to flag public functions lacking docstrings, causing CI pipelines to fail on violations. Language models are recommended only for drafting repetitive docstring stubs, while human review and automated checks together handle ownership and accuracy. The workflow aims to close the feedback loop that documentation has traditionally lacked compared to compiled or linted code.

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ProgrammingDEV Community ·

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