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Found 9,926 Skills
Perses variable lifecycle management: create Text and List variables at global, project, or dashboard scope. Handle variable chains with dependencies (A depends on B depends on C). Supports 14+ interpolation formats. Uses MCP tools when available, percli CLI as fallback. Use for "perses variable", "dashboard variable", "perses filter", "add variable". Do NOT use for datasource management (use perses-datasource-manage).
Context-driven aesthetic exploration with anti-cliche validation: typography, color, animation, atmosphere. Use when starting a frontend needing distinctive aesthetics, refreshing generic designs, or auditing for "AI slop" patterns. Use for "distinctive frontend", "unique aesthetics", "avoid generic design", "creative frontend". Do NOT use for quick prototypes, strict brand compliance, backend projects, or data visualization.
CUE schema authoring for Perses plugins: define data models, write validation constraints, create JSON examples, implement Grafana migration schemas in migrate/migrate.cue. Educational skill that explains CUE patterns specific to Perses plugin development. Use for "perses cue schema", "perses model", "plugin schema", "cue validation perses". Do NOT use for dashboard CUE definitions (use perses-dac-pipeline).
Run Python (ruff) and JavaScript (Biome) linting, formatting, and code quality checks with auto-fix support. Use when code needs linting, formatting, or style checking before commits. Use for "lint", "format", "ruff", "biome", "code style", or "check quality". Do NOT use for comprehensive code review (use systematic-code-review).
Meta-skill for combining Three.js, GSAP ScrollTrigger, React Three Fiber, Motion, and React Spring for complex 3D web experiences. Use when building applications that integrate multiple 3D and animation libraries, requiring architecture patterns, state management, and performance optimization across the stack. Triggers on tasks involving library integration, multi-library architectures, scroll-driven 3D experiences, physics-based 3D animations, or complex interactive 3D applications.
Checks manual test scripts for harness adoption, golden files, fail-fast, config sourcing, idempotency. Use when auditing manual test quality.
Google SEO APIs: Search Console (Search Analytics, URL Inspection, Sitemaps), PageSpeed Insights v5, CrUX field data with 25-week history, Indexing API v3, and GA4 organic traffic. Provides real Google field data for Core Web Vitals, indexation status, search performance, and organic traffic trends. Use when user says "search console", "GSC", "PageSpeed", "CrUX", "field data", "indexing API", "GA4 organic", "URL inspection", "google api setup", "real CWV data", "impressions", "clicks", "CTR", "position data", "LCP", "INP", "CLS", "FCP", "TTFB", or "Lighthouse scores".
This skill should be used when the user asks to "audit this codebase", "audit this code", "security audit", "code audit", "find vulnerabilities", "check for bugs", "review code quality", "find dead code", "check for anti-patterns", "performance audit", "check for code smells", "technical debt", or "code health check".
This skill should be used when the user asks to "create a blueprint", "blueprint this feature", "plan this implementation", "make a plan", "create an implementation plan", "design the architecture", "design this feature", or "break this down into steps".
Patient safety evaluation harness for healthcare application deployments. Automated test suites for CDSS accuracy, PHI exposure, clinical workflow integrity, and integration compliance. Blocks deployments on safety failures.
Coaches end-to-end ML system design interviews covering inference pipelines, recommendation systems, RAG, feature stores, and monitoring. Use for L6+ design rounds, ML architecture whiteboarding, system design practice, serving tradeoff analysis. Activate on "ML system design", "ML interview", "recommendation system design", "RAG architecture", "feature store design", "model serving". NOT for coding interviews, behavioral questions, ML theory quizzes, or paper implementations.
Solve competition math problems (IMO, Putnam, USAMO, AIME) with adversarial verification that catches the errors self-verification misses. Activates when asked to 'solve this IMO problem', 'prove this olympiad inequality', 'verify this competition proof', 'find a counterexample', 'is this proof correct', or for any problem with 'IMO', 'Putnam', 'USAMO', 'olympiad', or 'competition math' in it. Uses pure reasoning (no tools) — then a fresh-context adversarial verifier attacks the proof using specific failure patterns, not generic 'check logic'. Outputs calibrated confidence — will say 'no confident solution' rather than bluff. If LaTeX is available, produces a clean PDF after verification passes.