Run SonarQube/SonarCloud against production code to surface Code Smells, Bugs, and Maintainability ratings - the maintainability lens rather than the security lens. Production-only scope via sonar.exclusions; test code is reviewed separately. Use when a team wants maintainability and technical-debt ratings gating PRs, or when an existing SonarQube project reports numbers nobody has tied to a quality gate.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
SonarQube classifies issues across three software qualities - Reliability,
Maintainability, Security - and four Clean Code attributes
(Consistent, Intentional, Adaptable, Responsible) per the SonarSource
docs (see Issues introduction). qa-security-scanning's sonarqube-rules skill
covers the Security lens; this skill covers the Reliability +
Maintainability lens for production code.
| Stack | Scanner |
|---|---|
| Maven | sonar-maven-plugin (mvn sonar:sonar) |
| Gradle | org.sonarqube plugin (./gradlew sonar) |
| .NET | dotnet-sonarscanner |
| Anything else | sonar-scanner CLI |
See the SonarQube docs sitemap for per-build-tool installation.
Add to sonar-project.properties:
sonar.projectKey=acme.platform
sonar.sources=src
sonar.tests=tests,src/**/*.test.ts
sonar.exclusions=**/*.generated.*,**/migrations/**,**/vendor/**
sonar.test.inclusions=**/*.test.ts,**/*.spec.ts,tests/**
sonar.coverage.exclusions=**/*.generated.*,**/main.ts
Why separate sonar.tests vs sonar.sources: test code has different
quality expectations (long names, deliberate duplication for clarity,
Arrange-Act-Assert patterns). Lumping them into one scope produces
noise. Test code is reviewed separately.
# Local development scan against a SonarQube server
sonar-scanner \
-Dsonar.host.url=https://sonar.internal \
-Dsonar.token=$SONAR_TOKEN
# CI scan with PR analysis (branch + PR decoration)
sonar-scanner \
-Dsonar.pullrequest.key=$PR_NUMBER \
-Dsonar.pullrequest.branch=$PR_BRANCH \
-Dsonar.pullrequest.base=main
The scanner uploads to the configured server; results stream to the project dashboard.
| Metric | What it means | Sonar Way default |
|---|---|---|
| New Bugs | Reliability issues introduced in PR | 0 |
| New Code Smells | Maintainability issues introduced in PR | 0 |
| New Coverage | % new lines covered by tests | ≥ 80% |
| New Duplication | % new lines duplicated | ≤ 3% |
| Maintainability Rating (new code) | A - E based on debt ratio | A |
| Reliability Rating (new code) | A - E based on bug density | A |
Per Sonar Way QG: any condition fail blocks merge.
# GitHub Actions
- name: SonarQube Scan
uses: SonarSource/sonarqube-scan-action@v3
env:
SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
- name: SonarQube Quality Gate Check
uses: SonarSource/sonarqube-quality-gate-action@v1
timeout-minutes: 5
env:
SONAR_TOKEN: ${{ secrets.SONAR_TOKEN }}
The quality-gate-action polls the server until the gate result lands
and fails the build if it's RED.
| Anti-pattern | Why it fails | Fix |
|---|---|---|
Scan whole repo without sonar.tests separation | Test conventions flagged as smells; team disables Sonar | Split sonar.sources / sonar.tests (Step 2) |
| Apply gate to overall code, not new code | Legacy debt blocks all PRs forever | Use new-code-period gate (Sonar Way default) |
Mix this with the sonarqube-rules security settings | Two skills mutating same sonar-project.properties | This skill owns Reliability+Maintainability; sonarqube-rules owns the Security profile |
| Lower gate to merge pre-existing failures | Gate becomes meaningless | Use "Wont Fix" / "Accepted" issue resolution + scope-exclusion comment instead |
| Run after merge only | No PR decoration; hard to review | Run on PR with sonar.pullrequest.* flags (Step 3) |
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Builds a CI gate that fails the build on **new** WCAG / a11y violations introduced by a PR while grandfathering pre-existing violations on a per-rule / per-page baseline. Aggregates verdicts from axe-core / pa11y / Lighthouse a11y / WAVE / IBM Equal Access scans. Use when a project has accumulated a11y debt and a strict "zero violations" gate would block every PR - the ratchet pattern lets the team ship while preventing regressions.
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Workflow skill that builds an A/B-test validity checklist from an experiment proposal, walking the canonical design-correctness gates - pre-registered OEC/power/guardrails, randomization unit + SRM check, assignment integrity, telemetry, peeking discipline, novelty/primacy, post-experiment SRM re-check - into a per-experiment checklist + sign-off form. Use when launching, auditing, or governing an experiment. For pitfall mechanics (guardrails, peeking) see experiment-results-interpreter's references; to read an already-valid result use experiment-results-interpreter; for per-SDK harness tests use experiment-sdk-testing - this gates DESIGN, not SDK code.
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The single install-flow skill: the reference contract for the PWA install flow (installability gate fields, `beforeinstallprompt` handshake, per-platform paths - Android WebAPK / iOS Share menu / Firefox no-op - and the `display-mode` post-install signal, in references/install-flow-reference.md) plus the build-an-X workflow that emits the Add-to-Home-Screen suite. Walks the four-stage timeline, emitting one test per gate cell per [web.dev/articles/install-criteria][install-criteria], the deferred-prompt → `prompt()` → `userChoice` chain per [web.dev/articles/customize-install][customize-install], the iOS Safari manual-metadata branch (`apple-touch-icon`) per [web.dev/learn/pwa/installation][learn-pwa], and the post-install `(display-mode: standalone)` MQ assertion. Output: a Playwright spec with per-stage cells plus a coverage matrix. Use when a PWA's manifest, icons, or install handler change, when install conversion drops at an unknown stage, or when triaging a flaky install assertion.
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Build-an-X workflow that uses an LLM to map existing tests to spec sections - given a spec doc + the test suite, the LLM identifies which tests cover which sections, surfaces uncovered sections (gap), and recommends specific tests to add. Output is a coverage matrix per spec ID. Scope is mapping tests that already exist and naming the gaps, not authoring tests for new acceptance criteria. Use when a spec doc and a test suite both exist but nobody can say which requirements are actually covered - before a release sign-off, an audit, or a decision about where to spend the next round of test effort.
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Generates tests from natural-language specs (acceptance criteria, user stories, requirements) using an LLM, with confidence scoring per test case (LLM self-assessment plus heuristics: assertion quality, naming, completeness), batching uncertain cases for human review, and integration with the team's existing test framework. Use when the user asks to generate unit tests from acceptance criteria, convert user stories to test cases, automate test creation from requirements, or augment a spec-driven test suite with AI-generated stubs that are then curated before merge.
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Configures Allure Report (test-runner adapter install, `allure-results` directory wiring, `categories.json` for failure classification, `history-trend.json` retention via the copy-history-between-runs pattern), runs the Allure CLI to convert `allure-results` to a static HTML site, and uploads the report as a CI artifact. Use when the team needs richer test reporting than JUnit XML - step-level attachments, per-test history, retry tracking, and severity / epic / feature labeling across framework-agnostic adapters (pytest, Jest, JUnit, TestNG, NUnit, Mocha). As a rich static HTML report generator, it is the open-source alternative to the sunset ExtentReports (JVM/.NET per-test HTML narrative); for hosted cross-run flakiness analytics rather than a static per-run report use currents-integration.
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