118 skills · sorted by relevance
Turn a code pattern fixed in a pull request into a custom Go linter, a tool that checks code without running it. Covers a focused detection rule, tests, and registration in the linter runner.
Add custom Go code checkers to gh-aw, with guidance on tests, registration, and running all checks. Handle equivalent syntax consistently and optionally limit performance rules using test coverage, which records which code tests execute.
各プログラミング言語の既存リンターエコシステムを活用してカスタムlintルールを作成するスキル。 人間向けではなくAIエージェント向けのリンターであり、エラーメッセージはAIに対する修正指示プロンプトとして機能する。 Rust(dylint)、TypeScript/JavaScript(ESLint)、Python(pylint)、Go(golangci-lint)等、 言語ごとの標準的な方法でカスタムルールを `lints/` ディレクトリに作成する。 以下の場合に使用する: (1) プロジェクト固有のコーディングルールをAIに強制させたいとき、 (2) 違反時にAIが読める修正指示を出力するlintルールを作りたいとき、 (3) 命名規則・構造パターン・一貫性ルールをAI駆動のリンティングで強制したいとき。 トリガー: 「リンタールールを作成」「lintルールを追加」「このパターンを強制」 「AIリンター」「カスタムlint」「コードルール」「命名ルール」「構造ルール」 「create a linter rule」「add a lint rule」「enforce this pattern」「AI linter」。
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Check GenLayer intelligent contracts before testing. This skill uses the GenVM linter to find forbidden code patterns, SDK usage errors, and type mismatches, with JSON output for repeated fixes and commands to extract contract interface definitions.
Linting best practices and golangci-lint configuration for Golang projects — running linters, configuring .golangci.yml, suppressing warnings with nolint directives, interpreting lint output, and selecting linters. Use when configuring golangci-lint, asking about lint warnings or nolint suppressions, setting up code quality tooling, or choosing linters. Also use when the user mentions golangci-lint, go vet, staticcheck, or revive. Not for wiring a lint step into a GitHub Actions pipeline (→ See `samber/cc-skills-golang@golang-continuous-integration` skill).
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Use Metalint in .NET repositories that ship Node-based frontend assets and want one CLI entrypoint over several underlying linters. USE FOR: unified frontend lint commands; combined ESLint, Stylelint, HTMLHint, or similar checks; CI orchestration over multiple frontend linters. DO NOT USE FOR: simple repos where Biome already covers the required surface; teams that have not decided which underlying linters own each file type. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.
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Expert guide for Biome (Rust-based linter + formatter), ESLint/Prettier migration, and code quality tooling / Panduan ahli Biome (linter + formatter berbasis Rust), migrasi dari ESLint/Prettier, dan tooling kualitas kode.
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検査器（linter / ガード / CI ゲート / バリデータ / フィルタ）そのものの検出力が差分で静かに落ちていないか、また新設した検査が実際に検出できることが実証されているかを diff-time で検出する。Check 1 unverified detection reduction（検査器の検出ロジック（正規表現・除外パターン・解決集合・allowlist・baseline）を変更して検出件数が減ったのに、減った 1 件ずつが誤検出であった根拠が示されないまま「誤検出を潰した」「N → M 件に減少」と改善として主張している）、Check 2 unproven guard detection power（新しい検査ロジック・CI ゲート・バリデーションを追加・変更したのに、検出すべき入力を注入して検出されること／検出すべきでない入力で黙ることを示す変異注入の証跡が無く、「追加した」「CI が緑」を検出力の証拠として扱っている）、の 2 Check を対象とする report-only。テスト自身のアサーションが実質何も検証していない構造は test-assertion-effectiveness、レビュー基準・品質ゲートの明示的な弱体化（ルールの削除・閾値の引き下げ・suppression entry 追加・lint ルールの無効化）は review-criteria-integrity、リファクタ完了主張一般の検証は refactor-claim-audit、workflow の permissions と action pin は gha-workflow-security、設定ファイルの構文・型の妥当性は config-json へ委譲する
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Set up Plankton hooks in Claude Code to format and lint files after each edit. Route remaining violations to Claude for fixes, verify the results, and protect linter settings from changes that weaken checks.
Writes and reviews Lean 4 proofs, machine-checked arguments for mathematics or specifications. Follows Mathlib conventions to organize definitions and lemmas, fill proof gaps, refactor lengthy proofs, and establish automated checks for unproved claims and style.
Supabase security expert to audit RLS (Row Level Security), RBAC, relational databases, prevent data leakage, and utilize Supabase Linter / Ahli keamanan Supabase untuk audit RLS (Row Level Security), RBAC, database relasional, pencegahan kebocoran data, dan pemanfaatan Supabase Linter.
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Multi-language code quality validation (Python, JS/TS, Shell, SQL) — formatting, linting, type-checking, complexity analysis with auto language detection. Use when checking code quality or running linters. Trigger on "lint", "type-check", "quality check", "run the linters", "check code quality".
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[Quality] Use when a workflow step or the user asks for linters, formatters, type checks and static analysis in pre-commit and CI gates.
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Code quality dashboard. Wraps existing project tools (type checker, linter, test runner, dead code detector, shell linter), computes a weighted composite 0-10 score, and tracks trends over time. Use when: "health check", "code quality", "how healthy is the codebase", "run all checks", "quality score". (gstack)
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Turn a course plan into numbered exercise folders with problem, solution, and explanation variants. Create starter readme files, check naming and links with the project’s linter, and fix structural errors before committing.
Set up ESLint, a tool that checks JavaScript for errors and coding rule violations. Configure shared rules, connect checks to editors and automated workflows, and review flagged code alongside its behavior in the browser.
Prepare a repository for Claude Code on the web by creating a startup hook that installs project dependencies. Register the hook and check that it runs successfully, along with a sample test and code quality check.
Design the operating layer around a coding agent so it can read and edit code, run checks, and correct errors. Define completion criteria, permission boundaries, feedback, and recovery methods, and assess which tasks suit autonomous execution.
Set consistent Python conventions for naming, formatting, type checking, and documentation. Configure ruff and mypy or pyright, write clear function descriptions, and organize README and changelog content so a team can maintain shared standards.
Review GitHub Actions workflows for unsafe input handling, excessive token permissions, exposed secrets, and changeable action references. Get findings grouped by issue type, with severity ratings, exact YAML locations, and concrete fixes to review.
Route product questions to a specialist for prioritization, research, analytics, experiments, or implementation. Support recurring discovery by tracking interviews and assumption tests, checking how customer needs connect to proposed solutions, and returning results with a concise digest.
Build and review Kubernetes Operators, controllers that keep custom resources in their desired state. Included tools check resource definitions and Go reconciliation code, then assess operational capabilities and suggest improvements.
Review REST API specifications with automated checks for inconsistent conventions and breaking changes—changes that disrupt existing clients. Get a design grade, improvement recommendations, and tool reports to support release reviews and API migrations.
Review skill and agent definitions for structural issues and whether their instructions meet expected behavior. Four modes cover structure, test specifications, category criteria, and coverage reports that reveal missing specifications or checks.