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Found 25 Skills
Automated code review for pull requests using specialized review patterns. Analyzes code for quality, security, performance, and best practices. Use when reviewing code changes, PRs, or doing code audits.
You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C
Comprehensive checklist for conducting thorough code reviews covering functionality, security, performance, and maintainability
Performs comprehensive codebase analysis covering architecture, code quality, security, performance, testing, and maintainability. Use when user wants to audit code quality, identify technical debt, find security issues, assess test coverage, or get a codebase health check.
After an agentic task completes, perform a retrospective analysis across 6 dimensions (goal alignment, efficiency, decision quality, error handling, communication, reusability). Score performance, identify inefficiency patterns, evaluate skill usage, and produce actionable improvement recommendations. Triggers on "how did it go", "retrospective", "review performance", "what could be better", or after any long agentic task completes.
Turn vague "what did I do?" into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates. Uniquely mines Copilot CLI session logs to reconstruct forgotten work, plus git commits and GitHub PRs. Enforces a 3-part impact contract (action → result → evidence). Works standalone with zero dependencies. Trigger for: "brag", "log work", "what did I do", "backfill my work history", "performance review", "self-review", "self assessment", "write impact statement", "review prep", "promo packet", "promotion case", "weekly update", "status report", "accomplishments", "what did I ship", "I forgot to log my work", "summarize my work", "track my wins", "what should I highlight", "end of half", "career growth", "work journal", or any request to document, summarize, or organize work accomplishments.
Use this skill when designing OKR systems, writing performance reviews, running calibration sessions, creating PIPs, or building career ladders. Triggers on OKRs, performance reviews, calibration, PIPs, career ladders, leveling frameworks, feedback cycles, and any task requiring performance management system design.
Generates the Somnio HandShake Step 3 - Acknowledgement PDF document from raw evaluation notes. Use this skill whenever an Engineering Manager (EM) wants to create, generate, or produce one or more HandShake Acknowledgement documents, career review PDFs, seniority evaluation documents, or anything related to the Somnio bi-annual performance review process. Trigger even if the user says things like: generar el documento del handshake, armar el PDF de la evaluacion, crear el acknowledgement para un dev, generar el informe del career path, procesar estas fichas, or similar. The skill handles both single and batch (multiple devs) generation: it reads all attached ficha files, pre-fills what it can infer, confirms all data with the EM in a single table, then generates one PDF per dev.
You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C
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.
Master performance management, goal-setting, OKRs, reviews, feedback, and metrics for engineering teams
Review or refactor React / Next.js code for performance and reliability using a prioritized rule library (waterfalls, bundle size, server/client data fetching, re-renders, rendering). Use when writing React components, Next.js pages (App Router), optimizing bundle size, improving performance, or doing a React/Next.js performance review.