suggest-dfxp-fixes

To generate Python code fixes for DFXP TTML compliance report failures, this Skill analyzes the latest validation report to identify the most critical issue and produces a detailed code suggestion with file locations, tests, and spec references.

Automating fixes for missing MUST rules in TTML validation gaps is best handled by analyzing the latest compliance report to pinpoint the critical issue, then generating one precise Python fix per run with implementation notes and test coverage.

DFXP fix generation handles implementation caveats by analyzing the latest compliance report, identifying the most critical missing MUST rule or validation gap, and generating a targeted Python code fix with specific file locations and spec references.

Yes, you can automatically find the most critical issue in a DFXP compliance report, which then triggers the generation of a detailed Python code fix including line numbers, implementation notes, tests, and a ready-to-save markdown report.

To ensure a DFXP fix includes tests and spec references, the Skill analyzes the latest compliance report, generates the fix with specific file locations and line numbers, and outputs a ready-to-save markdown file guiding verification.

Yes, the generated TTML fix saves directly to ai_artifacts/compliance_checks/dfxp/suggested_dfxp_fixes.md, providing a ready-to-use markdown report that includes the code suggestion, tests, and verification guidance.