What problem does it solve? Quality numbers like coverage percentages and bug counts are routinely misused as quality gates or targets, which corrupts them and misleads stakeholders. This Skill provides precise metric definitions, baselining, counterweight pairing, and corruption checks so reported numbers survive being acted on. ## Core Features & Use Cases - Precise Metric Definitions: Formulas, data sources, time windows, exclusions, and distortions for pass rate, flake rate, escape rate, mutation score, suite duration, and more. - Anti-Metric Guardrails: A quarterly corruption checklist that detects Goodhart effects such as coverage rising while mutation score stays flat, or pass rate rising alongside skip counts. - Stakeholder Report Template: A worked quality report structure with trend tables, annotated events, data gaps, and interpretations with competing explanations. - Use Case: A QA lead asked to build a release-quality dashboard uses this Skill to define flake rate and escape rate precisely, baseline them over past releases, pair each metric with its counterweight, and present trends with caveats to engineering leadership. ## Quick Start Use the analyzing-quality-metrics skill to define and compute flake rate and escape rate from our CI history and issue tracker, then draft a stakeholder quality report for the last release.
