Compares implementation evidence against acceptance criteria and shows what is met, partial, missing, or untestable. Use when checking feature readiness, preparing QA sign-off, or turning criteria into a concrete verification matrix without inventing missing behavior.
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Verifies that the lines and branches a change actually touched are executed by tests, using LCOV or Cobertura diff coverage instead of whole-repo percentages, and escalates uncovered high-risk changes into a blocking finding. Use when a pull request needs a coverage gate that unrelated tests cannot satisfy, when total coverage looks healthy but the diff is untested, when wiring diff coverage into CI, or when someone claims a change is covered because the suite is green.
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Turns point-in-time quality readings into a trend: archives each run, diffs against the previous one, and reports direction per metric - practices newly present or regressed, coverage movement, flake rate, waivers expiring, eval scores - using limit/current/goal framing. Use when quality reporting is a series of disconnected snapshots, when a team needs to show improvement over a quarter, when a number is quoted with no baseline, or when a regression in the quality system itself should be visible.
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Analyzes diffs, changed files, hotfixes, and release candidates to identify where regression risk spreads and what must be retested first. Use when scoping retest after a change, reviewing QA impact for a pull request, or building a minimal confidence suite for release validation.
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