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Found 198 Skills
Validates SKILL.md files against Claude Code skill best practices. Checks conciseness, description quality, progressive disclosure, workflow structure, and common anti-patterns. Use when reviewing or auditing skills before shipping.
Automated, project-wide code coverage and CRAP (Change Risk Anti-Patterns) score analysis for .NET projects with existing unit tests. Auto-detects solution structure, runs coverage collection via `dotnet test` (supports both Microsoft.Testing.Extensions.CodeCoverage and Coverlet), generates reports via ReportGenerator, calculates CRAP scores per method, and surfaces risk hotspots — complex code with low test coverage that is dangerous to modify. Use when the user wants project-wide coverage analysis with risk prioritization, coverage gap identification, CRAP score computation across an entire solution, or to diagnose why coverage is stuck or plateaued and identify what methods are blocking improvement. DO NOT USE FOR: targeted single-method CRAP analysis (use crap-score skill), writing tests, running tests without coverage collection, applying test filters, producing TRX reports, or troubleshooting test execution (use run-tests for all of these).
Use when managing NixOS systems — rebuilding, configuring, deploying, installing, or building images. Covers flakes, modules, secret management, VM management, disk imaging, remote deployment, and common anti-patterns to avoid.
Reviews code for quality — architecture conformance, anti-patterns, performance issues, maintainability. Read-only analysis that detects circular dependencies, N+1 queries, dead code, naming violations, and layering breaches. Use when the user asks for a code review, wants feedback on code quality, PR review, tech debt analysis, or architecture conformance checks.
Use when layouts need to adapt to different screen sizes, iPad multitasking, or iOS 26 free-form windows — decision trees for ViewThatFits vs AnyLayout vs onGeometryChange, size class limitations, and anti-patterns preventing device-based layout mistakes
Expert Swift decisions Claude doesn't instinctively make: struct vs class trade-offs, @MainActor placement, async/await vs Combine selection, memory management pitfalls, and iOS-specific anti-patterns. Use when writing Swift code for iOS/tvOS apps, reviewing Swift architecture decisions, or debugging memory/concurrency issues. Trigger keywords: Swift, iOS, tvOS, actor, async, Sendable, retain cycle, memory leak, struct, class, protocol, generic
Use when writing Terraform for OCI, troubleshooting provider errors, managing state files, or implementing Resource Manager stacks. Covers terraform-provider-oci gotchas, resource lifecycle anti-patterns, state management mistakes, authentication issues, and OCI Landing Zones.
Run ESLint with security plugins on JavaScript/TypeScript code. Detects eval usage, non-literal RegExp, prototype pollution, and other JS/TS security anti-patterns.
Detect common code smells and anti-patterns providing feedback on quality issues a senior developer would catch during review. Use when user opens/views code files, asks for code review or quality assessment, mentions code quality/refactoring/improvements, when files contain code smell patterns, or during code review discussions.
Identify security vulnerabilities and anti-patterns providing feedback on security issues a senior developer would catch. Use when user mentions security/vulnerability/safety concerns, code involves user input/authentication/data access, working with sensitive data (passwords/PII/financial), code includes SQL queries/file operations/external API calls, user asks about security best practices, or security-sensitive files are being modified (auth, payment, data access).
Creates and manages Biome GritQL custom lint rules to enforce coding patterns. Use when creating linter rules, enforcing code conventions, preventing anti-patterns, or when the user mentions Biome, GritQL, custom lint rules, or AST-based linting.
Analyze codebases for anti-patterns, code smells, and quality issues using ast-grep structural pattern matching. Use when reviewing code quality, identifying technical debt, or performing comprehensive code analysis across JavaScript, TypeScript, Python, Vue, React, or other supported languages.