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Found 372 Skills
Help users create high-quality skills by discovering and incorporating proven methodologies from domain experts. Use this skill BEFORE skill-creator when users want to create a new skill - it enhances skill-creator by first identifying expert frameworks and best practices to incorporate. Triggers on requests like "help me create a skill for X" or "I want to make a skill that does Y". This skill guides methodology selection, then hands off to skill-creator for the actual skill generation.
QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the data.
Define your Method — the unique methodology you use to deliver your transformation. This is the third element of the World Code framework. Use when someone says "define my method", "my methodology", "how I solve problems", "unique approach", or "method element".
Query the bundled research knowledge graph for methodology guidance. Routes questions through a 3-tier knowledge base — WHY (research claims), HOW (guidance docs), WHAT IT LOOKS LIKE (domain examples) — plus structured reference documents. Returns research-backed answers grounded in specific claims with practical application to the user's system. Triggers on "/ask", "/ask [question]", "why does my system...", "how should I...".
Four common skill archetypes with structure templates - CLI reference, methodology, safety/security, and orchestration. Use when creating new skills to select appropriate structure.
Technical research methodology with YAGNI/KISS/DRY principles. Phases: scope definition, information gathering, analysis, synthesis, recommendation. Capabilities: technology evaluation, architecture analysis, best practices research, trade-off assessment, solution design. Actions: research, analyze, evaluate, compare, recommend technical solutions. Keywords: research, technology evaluation, best practices, architecture analysis, trade-offs, scalability, security, maintainability, YAGNI, KISS, DRY, technical analysis, solution design, competitive analysis, feasibility study. Use when: researching technologies, evaluating architectures, analyzing best practices, comparing solutions, assessing technical trade-offs, planning scalable/secure systems.
This skill should be used when the user wants to "run an evaluation", "evaluate my ADK agent", "write an evalset", "debug eval scores", "compare eval results", or needs guidance on ADK (Agent Development Kit) evaluation methodology and the eval-fix loop. Covers eval metrics, evalset schema, LLM-as-judge, tool trajectory scoring, and common failure causes. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for API code patterns (use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).
Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (see golang-benchmark skill) or debugging workflow (see golang-troubleshooting skill).
Troubleshoot Golang programs systematically - find and fix the root cause. Use when encountering bugs, crashes, deadlocks, or unexpected behavior in Go code. Covers debugging methodology, common Go pitfalls, test-driven debugging, pprof setup and capture, Delve debugger, race detection, GODEBUG tracing, and production debugging. Start here for any 'something is wrong' situation. Not for interpreting profiles or benchmarking (see golang-benchmark skill) or applying optimization patterns (see golang-performance skill).
Golang benchmarking, profiling, and performance measurement. Use when writing, running, or comparing Go benchmarks, profiling hot paths with pprof, interpreting CPU/memory/trace profiles, analyzing results with benchstat, setting up CI benchmark regression detection, or investigating production performance with Prometheus runtime metrics. Also use when the developer needs deep analysis on a specific performance indicator - this skill provides the measurement methodology, while golang-performance provides the optimization patterns.
Official Feature-Sliced Design (FSD) v2.1 skill for applying the methodology to frontend projects. Use when the task involves organizing project structure with FSD layers, deciding where code belongs, defining public APIs and import boundaries, resolving cross-imports or evaluating the @x pattern, deciding whether logic should remain local or be extracted, migrating from FSD v2.0 or a non-FSD codebase, integrating FSD with frameworks, or implementing common patterns such as auth, API handling, Redux, and React Query within FSD.
Systematically evaluate scholarly work using the ScholarEval framework, providing structured assessment across research quality dimensions including problem formulation, methodology, analysis, and writing with quantitative scoring and actionable feedback.