cgs.qa.report

Automate QA report generation by running E2E and visual tests, then compiling results and LLM-driven analysis into a timestamped markdown report. This delivers a comprehensive overview of feature readiness.

LLM-based visual investigation analyzes detected UI mismatches after visual regression tests run. It evaluates discrepancies against expected designs to provide automated analysis of visual differences within the generated QA report.

Yes, you can filter end-to-end tests by story ID when running a QA pass. This allows you to target specific feature scopes and generate focused reports for individual user stories.

Yes, you can skip visual comparisons during test execution. This allows you to run functional end-to-end tests only, speeding up the QA pass when visual regression checks are not required.

An automated markdown QA report includes compiled end-to-end test results, visual discrepancies, LLM-driven analysis of mismatches, and a release recommendation. It is timestamped for tracking feature readiness over time.

Yes, it generates a release recommendation after running E2E and visual tests. By analyzing functional test results and visual discrepancies, it compiles a release recommendation into the final timestamped markdown report.