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Found 35 Skills
Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.
Go-specific code review with 6-phase methodology: Context, Automated Checks, Quality Analysis, Specific Analysis, Line-by-Line, Documentation. Use when reviewing Go code, PRs, or auditing Go codebases for quality and best practices. Use for "review Go", "Go PR", "check Go code", "Go quality", "review .go". Do NOT use for writing new Go code, debugging Go bugs, or refactoring -- use golang-general-engineer, systematic-debugging, or systematic-refactoring for those tasks.
This skill should be used when the user asks to "review code", "code review", "check my code", "audit code", "find bugs", "security review", "performance review", or any ServiceNow code quality assessment.
Analyze code examples in SKILL.md files for correctness using static analysis and TypeScript compilation
Run a full Dune app platform review against a React/TypeScript CDF codebase, following the cognitedata/dune-app-reviews scoring criteria. Produces three artifacts: review-files.md (per-file inventory), review-packages.md (dependency audit), and review-report.md (scored report with must/should/nice-fix items). Use when the user asks for a Dune app review, pre-submit review, approval review, app certification review, code quality audit, CDF platform review, or "run dune-review" on a codebase before submission.
Use when the user asks to perform a code review, review code changes, analyze a diff, or audit code quality. Runs a structured review of git diff output covering security, correctness, performance, maintainability, and style. Produces a markdown report saved as a .md file named after the current branch.
· Audit AI-generated code slop: hallucinated APIs, over-abstraction, duplicate code, test theater, noisy comments. Triggers: 'slop', 'AI-generated code', 'cleanup', 'overengineered'. Not for prose (use anti-ai-prose).
Load PROACTIVELY when task involves reviewing code, auditing quality, or validating implementations. Use when user says "review this code", "check this PR", "audit the codebase", or "score this implementation". Covers the 10-dimension weighted scoring rubric (correctness, security, performance, architecture, testing, error handling, type safety, maintainability, accessibility, documentation), automated pattern detection for anti-patterns, and structured review output with actionable findings.
Validates and scores Claude Code skill packages for quality, completeness, and best practices compliance. Tests Python scripts, checks YAML frontmatter, and generates quality reports. Use when creating new skills, validating skill packages, or auditing skill quality.
Run a comprehensive Go-to-Market and launch readiness review for a project phase. Combines marketing content audit, code quality review, performance audit, accessibility audit, infrastructure readiness, and business review with council evaluation. Use before phase launches or when GTM review issues are ready.
Systematically find blind spots in code, architecture, APIs, and deployment — structured critique that catches what familiarity hides
Code quality gatekeeper and auditor. Enforces strict quality gates, resolves the AI verification gap, and evaluates codebases across 12 critical dimensions with evidence-based scoring. Use when auditing code quality, reviewing AI-generated code, scoring codebases against industry standards, or enforcing pre-commit quality gates. Use for quality audit, code review, codebase evaluation, security assessment, technical debt analysis.