Run Lizard against production source to enforce per-function cyclomatic complexity (CCN), NLOC, and parameter-count thresholds - language-agnostic (30+ languages). Scoped to production code via `-x"./tests/*"`; test complexity is reviewed separately. Use when a codebase spans several languages and needs one complexity gate across all of them, or when a function has grown unreviewable and the team wants a numeric threshold in CI.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Lizard analyzes source code per function for NLOC (non-comment LoC), CCN (cyclomatic complexity), token count, and parameter count across 30+ languages including C/C++, Java, Python, JavaScript, Go, Rust, TypeScript, Swift, Kotlin (per the Lizard README). Default CCN warning threshold is 15.
pip install lizard
Or run the standalone script:
python lizard.py path/to/code
Per the Lizard README, no external deps required.
lizard src/
Default output groups by file with per-function NLOC/CCN/token/param counts. Default warning threshold: CCN ≥ 15.
lizard src/ \
-x"./tests/*" \
-x"./vendor/*" \
-C 10 \
-L 100 \
-a 5
| Flag | Meaning |
|---|---|
-x PATTERN | Exclude (must include tests/** for production-only scope) |
-C N | CCN warning threshold (default 15; tighten to 10 for new codebases) |
-L N | Max function NLOC (default 1000; tighten to 80 - 100) |
-a N | Max parameter count (5 = "if you need more, pass an object") |
# CSV for grep / jq pipelines
lizard src/ -x"./tests/*" -C 10 --csv > lizard.csv
# XML for CI parsers (cppncss-style)
lizard src/ -x"./tests/*" -C 10 -X > lizard.xml
# HTML for human review
lizard src/ -x"./tests/*" -C 10 -H > lizard.html
lizard src/ -x"./tests/*" -C 10 -L 100 -a 5 -w
EXIT=$?
if [ "$EXIT" -ne 0 ]; then
echo "Complexity threshold breached. See report."
exit 1
fi
-w prints warnings only (clang/gcc style). Lizard exits non-zero
when any function exceeds the configured threshold.
# Only Python
lizard src/ -l python -C 10
# Only TypeScript + JS
lizard src/ -l typescript -l javascript -C 10
Useful when a polyglot repo has language-specific budgets (e.g., Python tolerates higher CCN than C).
| Anti-pattern | Why it fails | Fix |
|---|---|---|
| Run on whole repo including tests | Test setup helpers ("create user with 12 fields") look complex; tests get refactored away from clarity | Always exclude tests/, spec/ (Step 3) |
| Set CCN threshold to default (15) | Too lax for new code | Start at 10 for new code; track existing code as baseline |
| Block PRs on absolute count | Legacy code can't add a single line | Diff-only: scan PR-changed functions only with git diff --name-only filter |
| Refactor for CCN at expense of clarity | Splitting a clear linear function into 4 helpers raises overall complexity | Use CCN as a smell signal, not a hard rule |
| Skip parameter-count guard | "God functions" with 12 args slip through | -a 5 enforces object-arg style |
sonarqube-maintainability-gate for cognitive
complexity if needed.まだレビューはありません。使ってみた感想をお寄せください。
ログインなしで書き込めます。使ってみた感想、質問、動かなかった環境などを気軽にどうぞ。
まだコメントはありません。最初のコメントを書いてみませんか。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。