Test-First AI Documentation: A Workflow That Keeps Generated Docs Honest
AI code assistants have made documentation fast to produce and easy to ignore. The issue is not speed; it's trust. Models can write a polished docstring that describes a function that no longer exists, or an example that fails on the first run. The more docs we generate, the more stale those docs become if nothing checks them. This article describes a test-first documentation workflow. It treats…
In the rapidly evolving world of AI code assistants, documentation often suffers from trust issues. Generated documentation can describe non-existent functions or include failing examples. To address this, the article introduces a test-first documentation workflow that treats documentation like code. Each claim goes through automated checks before being finalized. The workflow comprises three test gates and a separation of duties between AI and human reviewers.
Gate 1, Presence, ensures every public function has a docstring using tools like pydocstyle or custom AST scripts. Any new function without a docstring triggers a CI failure. Gate 2, Accuracy, requires docstring examples to be executable. Python's doctest and custom checks are used to validate examples. If a function's behavior changes, the docs fail. Gate 3, Freshness, flags docstrings when function signatures change. A CI script compares public names defined in the code with those mentioned in the documentation.
The workflow also separates the drafting process from ownership. AI drafting, such as using MonkeyCode, handles repetitive tasks like generating docstring stubs. However, humans are responsible for reviewing ownership aspects. These include public API contracts, breaking changes, security and safety invariants, and rationale for design decisions. A table in the article summarizes what AI can draft and what humans must review.
In summary, this test-first documentation workflow ensures generated AI docs remain honest by enforcing presence, accuracy, and freshness checks. By separating drafting and review responsibilities, the workflow reduces the risk of stale or incorrect documentation.
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