Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add pnakhat/qa-ai-repo --skill jest-coverage-mutationgit clone --depth 1 https://github.com/pnakhat/qa-ai-repoWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/pnakhat/qa-ai-repo/jest-coverage-mutation)<a href="https://agentmods.dev/skills/pnakhat/qa-ai-repo/jest-coverage-mutation"><img src="https://agentmods.dev/badge/skills/pnakhat/qa-ai-repo/jest-coverage-mutation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/pnakhat/qa-ai-repo/jest-coverage-mutation"><img src="https://agentmods.dev/badge/skills/pnakhat/qa-ai-repo/jest-coverage-mutation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00130 | $0.01716 |
| Opus 5 | $0.00065 | $0.00858 |
| Sonnet 5 | $0.00026 | $0.00343 |
| Haiku 4.5 | $0.00013 | $0.00172 |
Grade A, and why
jest-coverage-mutation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jest Coverage & Mutation Testing
Coverage tells you what code ran during tests. Mutation testing tells you
whether your tests would catch a bug in that code. You need both: coverage to
find untested code, mutation to find weakly tested code (executed but not
asserted). See reference.md for config, a worked survivor example, and commands.
Coverage vs mutation — what each proves
| Question | Coverage answers | Mutation answers |
|---|---|---|
| Did this line execute in a test? | ✅ yes/no | — |
| Did a test assert on its behavior? | ❌ can't tell | ✅ yes/no |
| Would a real bug here be caught? | ❌ can't tell | ✅ yes/no |
Is the boundary (> vs >=) pinned down? |
❌ can't tell | ✅ yes/no |
| Cost to run | cheap (one pass) | expensive (N re-runs) |
Coverage is the floor (find code no test touches). Mutation score is the quality bar (find code no test verifies). Report the mutation score, never coverage % alone.
The core idea
- Line/branch coverage can be 100% with zero real assertions — a test that calls a function but checks nothing still "covers" it.
- Mutation testing deliberately introduces small faults ("mutants") into the
source (e.g.
>→>=,+→-,true→false, remove a statement) and re-runs the tests. If a test fails, the mutant is killed (good). If tests still pass, the mutant survived — a real bug would have slipped through. - Mutation score = killed / (killed + survived), ignoring no-coverage and invalid mutants. This is your real test-effectiveness metric.
Workflow — coverage first, then mutation
- Coverage first (cheap). Turn on Jest coverage with a sensible
coverageThresholdandcollectCoverageFromscoped to source (not tests/ configs). Fix the obvious gaps — untested files, uncovered branches. - Then mutation (where it matters). Run Stryker on the high-value / high-risk modules (business logic, calculations, validators, reducers). Don't mutate the whole repo on day one — it's slow.
- Read the survived mutants. Each survivor points at a specific weak spot: the code path is executed but the assertion doesn't pin down the behavior.
- Kill mutants by strengthening tests, not by deleting mutators:
- Add/tighten assertions (assert the value, not just "no throw").
- Cover boundary conditions the mutant exposed (
>=vs>, off-by-one). - Add missing negative/error cases.
- Set thresholds and gate CI. Fail the build below a mutation
breakthreshold on the modules you've committed to; ratchet it up over time.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 120 lines · 130 tokens per session scan A aa6beb18955d
jest-coverage-mutation is a skill published in the GitHub repository pnakhat/qa-ai-repo (2 stars, last pushed 2mo ago), licensed MIT. It adds 130 tokens to every session and 1,716 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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