Spec Compliance Audit

Spec compliance validation derives literal acceptance assertions from your plan and verifies them using ast.parse, targeted grep, and pytest collection on Python modules. This proves the implementation matches the written specification rather than merely confirming expected file locations exist.

AST-driven signature verification uses ast.parse to confirm that class and method constructor parameters match the plan. It proves that symbols exhibit the correct behavior and structure, ensuring the implementation is compliant rather than just present in the codebase.

Code reviews often pass falsely because they only check if expected file paths exist. A true spec compliance audit applies an anti-self-report trust policy, treating previous outputs as inputs to re-verify with deterministic grep and AST checks, preventing fake implementations from passing.

You convert each specification promise into an explicit acceptance-assertion table containing re-runnable commands. This deterministic mapping allows you to systematically apply grep, wc -l, and ast.parse checks to validate that every spec requirement is implemented in the code.

Yes, you can use targeted grep and ast.parse to verify that promised security mitigations have corresponding tests and correct code structures. This ensures security guardrails are actually implemented and that fake implementations do not pass the compliance audit.

Grep audits are limited to finding text matches and cannot verify structural correctness alone. For comprehensive spec compliance, grep must be combined with ast.parse to validate constructor parameters and pytest collection to ensure the behavior matches the specification.