Doc Drift Is a Bug: A Claim-Checking Loop for Model-Generated Docs
Generated docs fail most often at the boundary between prose and code, where a flag name or a signature silently disagrees with the source. A free-tier model can draft that prose quickly, but the disagreement is a bug that better prompting alone will not fix. The reliable fix is a verification loop that extracts mechanical claims from the doc and diffs them against the source tree. A human then…
Model-generated documentation often contains inaccuracies when it comes to mechanical claims, such as flag names, defaults, argument arity, and function signatures. These inaccuracies occur because the model generalizes from similar tools rather than reading the actual source code. To address this issue, a verification loop can be implemented to extract mechanical claims from the documentation and compare them against the source tree.
This loop consists of five stages: drafting, extracting, verifying, diffing, and reviewing. The drafting stage involves a free-tier model generating a first-pass reference document from the source tree. The extraction stage pulls mechanical claims from the Markdown documentation, while the verification stage retrieves the ground truth from the Python Abstract Syntax Tree (AST).
The diffing stage compares the extracted claims with the source code and generates a drift report. Finally, a human reviews the semantic sections and provides the final sign-off. By implementing this verification loop, the cost of the pipeline remains near zero, as it can be run on a free server. This approach ensures that only the semantic parts of the documentation require human review, while the mechanical claims are automatically checked for accuracy.
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