gpd-regression-check

Run automated re-verification on verified targets across completed research phases to detect regressions and identify inconsistencies. This ensures notation drift, convention changes, and approximation regime violations are caught and reported.

Notation drift breaks project consistency when modified conventions invalidate previously verified derivations and shared equations. Cross-phase consistency checks parse historical artifacts to detect these regressions and verify shared derivation integrity.

Run automated validation scripts to verify the existence and substantiveness of referenced files and equations, ensuring artifact integrity. This detects missing or invalid referenced artifacts across completed research phases.

Yes, a GPD runtime environment and Python are required to execute regression detection checks. The Skill utilizes Python libraries and command-line tools to parse data and validate claims within this specific runtime.

Yes, you can limit regression detection scope to a single phase by specifying the phase number as a command-line argument. Without arguments, the script defaults to re-checking all completed phases for regressions.

The best way to maintain research integrity when modifying approximation regimes is to run automated cross-phase consistency checks. This re-verifies decisive evidence and shared derivations to ensure modifications do not introduce regressions.