Measure and improve test coverage meaningfully. Covers Istanbul/V8/coverage.py configuration, coverage gap analysis by risk, coverage-as-ratchet in CI (never let it decrease), PR coverage diff checks, mutation testing for assertion quality, and distinguishing meaningful from vanity coverage. Use whe

<objective A suite at 90% line coverage with assertion free tests catches zero bugs — line coverage proves code ran, not that a regression would be caught. This skill measures the right things (branch coverage, mutation score, critical path coverage), gates them in CI with a ratchet so coverage can only go up, and surfaces gaps by risk instead of chasing a vanity number. It prevents the classic failure: a green coverage badge over a test suite that never asserts anything meaningful, while the payment module sits at 30%. </objective Quick Route Situation Go to Pick and configure a coverage provider Coverage Tools → references/tool config.md Decide where to write tests next Gap Analysis Stop coverage from regressing in CI Coverage as CI Gate → Ratchet Pattern Show per PR coverage to reviewers Coverage as CI Gate → PR Diff Tests run code but don't assert Mutation Testing Decide what to exclude / what target to set Meaningful vs Vanity Coverage Discovery Questions Check .agents/qa project context.md first — if it exists, use it and skip anything already answered there. Then: 1. What test runner and coverage tooling is configured? Check for vitest.config. (coverage block), jest.config. (coverageProvider), .nycrc , c8 in scripts, or [tool.coverage] in pyproject.toml . The runner decides the install — Vitest pulls @vitest/coverage v8 , not c8 (see Coverage Tools). 2. What is the current coverage level? Run the existing coverage command and note line, branch, and function percentages. This is the baseline for the ratchet. 3. Is coverage gated in CI? Check GitHub Actions / GitLab CI for coverage , coverageThreshold , fail under , or cov fail under . No gate means coverage is decorative. 4. What is the target, and who set it? A target without rationale ("the VP said 80%") leads to gaming. Targets should reflect risk tolerance and codebase maturity, not a round number. Core Principles 1. Coverage measures breadth, not depth. A line being executed does not mean it is tested correctly. expect(true).toBe(true) executes the function but asserts nothing. Coverage tells you what code ran, not whether the tests would catch a bug — that is what mutation testing measures. 2. Branch coverage matters more than line coverage. A ternary condition ? a : b on one line counts as fully covered in line coverage even if only one branch ran. Line coverage does not guarantee branch coverage. Gate on branches, not just lines: 3. Ratchet pattern: never decrease, only increase. Record current coverage as the minimum threshold. Every PR must meet or exceed it. Coverage climbs over time without forcing an artificial target up front. 4. Focus on gaps by risk, not on the number. A project at 85% is not automatically "better" than one at 75%. What matters is whether the untested slice contains payment, auth, or data integrity logic. Analyze gaps by risk. 5. New code has a higher bar than legacy code. Require 90%+ on new code in PRs even if the project sits at 65%. This stops coverage decay without demanding a rewrite of legacy code. Coverage Tools Pick the provider by test runner first , then by how cleanly it maps to your build output. Runner / context Install Provider Vitest @vitest/coverage v8 (default) or @vitest/coverage istanbul coverage.provider: 'v8' / 'istanbul' Jest bundled ( coverageProvider: 'v8' or 'babel' ) V8 or Istanbul/babel Non Vitest Node ( node:test , plain mocha) c8 CLI V8 via c8 <command Legacy Istanbul CLI nyc Istanbul instrumentation Python pytest cov (wraps coverage.py) coverage.py Two engines underneath: V8 coverage — built into the V8 engine, so it does not instrument source: faster, no Babel transform. For Vitest, install @vitest/coverage v8 (NOT c8 — that is the standalone CLI for non Vitest runners). For a plain node:test or mocha project, c8 is the CLI wrapper around the same V8 data. Default for new Node/Vitest projects. Istanbul — instruments source code; slower but maps more reliably through transpilers and bundlers. Switch to it ( @vitest/coverage istanbul , or nyc ) when V8 maps poorly. Symptom that V8 maps poorly: reported uncovered lines land on blank lines, closing braces, or decorators, or whole covered functions show as red — that means the source map is misattributing lines (common with certain TS bundlers / SWC configs). When you see that, flip to the Istanbul provider. Node baseline: c8 11.x and nyc 18.x are current. c8 11 still supports Node =12; nyc 18 requires Node 20 = 22 . If you must stay on Node 18, pin nyc@^17 (c8 11 runs fine on Node 18). New projects should standardize on Node 20+. See references/tool config.md for the full provider configs (Vitest coverage block, .nycrc.json , Jest coverageThreshold , pyproject.toml / .coveragerc.toml ), install commands, and run invocations. Merging coverage across test types Unit, integration, and E2E runs each produce partial coverage. Combine them so a line covered only by an integration test isn't reported as a gap: Vitest — run as multiple projects/configs and let Vitest merge, or merge coverage final.json outputs. nyc — nyc merge .nyc output merged.json && nyc report t merged combines .json files from separate runs. coverage.py — coverage combine after running each suite with coverage run p . Merge first, gate on the merged total. Don't gate each suite's coverage in isolation. Coverage Report Types Reporter Output Use Case text Terminal table Quick local check html Interactive HTML Detailed local analysis, clicking through files lcov lcov.info file SonarQube, Codecov, Coveralls integration json summary coverage summary.json CI scripts, PR comments, dashboard metrics cobertura cobertura coverage.xml GitLab CI coverage visualization Gap Analysis Coverage reports show which lines and branches did not run. Not all gaps are equal — prioritize by risk. Step 1: Generate the report. Step 2: Sort files by uncovered lines. Parse coverage summary.json , sort files by (total covered) descending, focus on the top 20. A small script that reads the JSON summary and outputs file / line% / branch% / uncovered count makes this repeatable. Step 3: Map gaps to risk. Gap Location Risk Level Action Payment processing Critical Write tests immediately Auth/permissions Critical Write tests immediately Data validation High Add to next sprint Error handling paths High Add to next sprint Utility functions Medium Cover when modifying UI formatting Low Skip unless regression prone Generated code None Exclude from coverage Include branch coverage in the sort, not just lines — a file at 100% line / 50% branch hides untested paths a line only sort would rank as "done." Coverage as CI Gate Threshold Configuration Set a global threshold as the project minimum, then layer per directory thresholds stricter for critical code (payments, auth) than for utilities. Vitest uses glob keys under thresholds (e.g. "src/payments/ ": { lines: 95, branches: 90 } ); Jest uses path keys under coverageThreshold . Both support per path overrides. See references/ci gating.md for the global, per directory, and Jest per file threshold config. Ratchet Pattern Never let coverage decrease. Record the current level as the minimum and floor it upward when coverage improves. A ratchet script reads coverage summary.json , compares each metric against a committed .coverage ratchet.json , fails the build on any regression, and updates the baseline when coverage improves. Commit .coverage ratchet.json (e.g. { "lines": 82, "branches": 78, ... } ). In CI, run the ratchet script after tests. On main branch merges, auto commit the updated ratchet file if coverage improved. See references/ci gating.md for the full coverage ratchet.ts script. PR Diff Coverage Gate Require new code in a PR to meet a higher threshold (e.g. 90%) than the project baseline. In CI, use git diff name only origin/main...HEAD to identify changed files, then check their coverage from coverage summary.json . Fail the pipeline if changed file coverage falls below the threshold. This stops decay without rewriting legacy code. Surface the diff to reviewers with davelosert/vitest coverage report action@v2 (reads the JSON summary) or marocchino/sticky pull request comment@v2 with a script that filters to changed files. See references/ci gating.md for the full PR workflow. Hosted alternatives: Codecov , Coveralls , and Trunk Coverage ship first class differential PR coverage with merge blocking gates and inline annotations. Most teams prefer these over hand rolled diff scripts — pick one if you don't already have a coverage host. Codecov + GitHub: codecov/codecov action@v5 reads lcov.info and posts a PR diff comment automatically. Mutation Testing Mutation testing measures assertion quality , not just code execution. It mutates your source (flips a to = , deletes a line) and checks whether a test fails. A surviving mutant means a real bug your tests would miss. With Stryker JS v9.6+ and Vitest 4.1+ the cost is low enough to run on PR changed files; mutmut 3.x covers Python. Targeting Mutation testing is expensive on whole codebases — run it incrementally . Stryker's incremental: true (JSON cache) plus mutate scoped to the git diff re mutates only touched files; mutmut similarly mutates per path. Restrict to: Pure business logic (validators, calculators, transformers) Critical paths (payment, auth, data integrity) Code with high line coverage but suspect assertions (branch coverage 90% but few assertion variants) Skip UI rendering, glue code, and generated code. See references/mutation testing.md for the Stryker config ( stryker.config.json , incremental, run on changed files only) and the mutmut invocation. Reading the score A mutation score of 80% means 80% of injected bugs were caught. Lower than your coverage % is normal — many mutants land in untested branches the coverage report already flagged. The interesting signal is high coverage + low mutation score : code executes but assertions don't constrain it. Meaningful vs Vanity Coverage Why 100% Coverage Is Usually Wrong 100% requires testing every branch of every line, including: Error handling for impossible states Default cases in exhaustive switches Framework lifecycle methods never called directly Defensive checks against corrupted data Tests written to hit 100% are often trivial, brittle, and catch no real bugs. Diminishing Returns Coverage Range Value Effort 0% to 60% High — main paths, obvious regressions Low 60% to 80% Medium — error paths, edge cases Medium 80% to 90% Lower — unusual combinations, defensive code High 90% to 100% Minimal — unreachable code, framework internals Very high The sweet spot is 75–85% for most projects. Critical paths (payments, auth) aim higher ( 90%+ ). Set the global threshold in the sweet spot and per directory thresholds at 90%+ for payment/auth. What NOT to Cover Exclude these — they inflate the denominator without adding value. Document each exclusion's justification in a CONTRIBUTING/coverage note so the exclude list can't quietly hide real gaps. Quality Indicators Beyond Percentage Indicator What It Measures How to Get It Mutation score Would tests catch a real bug? Stryker / mutmut Branch coverage Are all conditional paths tested? V8/Istanbul with branch reporting Critical path coverage Are payment/auth/data flows fully covered? Per directory thresholds Defect escape

coverage-analysis