14.5K skills · sorted by relevance
Build a backend service or an end-to-end frontend/backend integration when service/API/data boundaries are the primary deliverable; do not trigger for pure UI, contract design only, security review, test workflow, or every feature touching both folders.
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Run a non-destructive open-source, npm, or public release readiness checklist covering package metadata, provenance, license, internal artifact exposure, and dry-run evidence; complements security, shipping, and sanitizer reviews, and must not publish, delete, rewrite history, or mutate release state.
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Create, edit, fix, or explain Mermaid diagrams for relationships, decision branches, interactions, lifecycles, and data models; also use when the parent selects a diagram to materially clarify an explanation. Do not trigger for simple status, one fact, short lists, quantitative charts, or marketing slides.
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Structure source-grounded consulting-style analysis for strategy, market, product, operations, or decision memos. Use for MECE problem framing, hypotheses, options, tradeoffs, executive recommendations, or "consulting analysis" requests; do not use for legal/financial advice, implementation, data computation, chart rendering, or unsourced business claims.
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Idiomatic Go concurrency - sync primitives, channel semantics, the select statement, and the standard channel patterns (cancellation/done-channel, fan-out/fan-in, pipeline, or-done, context, worker-pool). Use when writing or reviewing Go that spawns goroutines, shares state, or coordinates over channels, even if the user never says "concurrency" - e.g. data races, deadlocks, goroutine leaks, sync/context/select usage, or "make this parallel". Distilled from luk4z7/go-concurrency-guide.
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Produces comprehensive system architecture plans for features and products including component breakdown, data flow diagrams, system boundaries, API contracts, and scaling considerations. Use for "system design", "architecture planning", "feature design", or "technical specs".
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Analyzes and optimizes SQL queries using EXPLAIN plans, index recommendations, query rewrites, and performance benchmarking. Use for "query optimization", "slow queries", "database performance", or "EXPLAIN analysis".
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Implements TanStack Query (React Query) for server state management with caching, mutations, optimistic updates, and infinite queries. Use when users request "react query", "tanstack query", "data fetching", "cache management", or "server state".
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Deep competitive intelligence for any market. Analyzes competitors' products, pricing, customer sentiment, GTM strategy, and growth signals using real web data. Produces battle cards, pricing landscape, and feature matrix. Use when the user wants to understand their competitive landscape, analyze competitors, compare products in a market, or research who they're competing against. Triggers for "who are my competitors", "competitive analysis", "competitor research", "battle cards", "pricing comparison", "competitor pricing", "market players", "competitive intelligence", "competitive landscape", "who else is in this space", "competitive moat", or any request to profile, compare, or map competitors in a category. Works standalone — no prior startup-design session needed.
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UI/UX design intelligence for web, mobile, and desktop. This skill should be used when designing, building, reviewing, or fixing interfaces, including pages, components, design systems, accessibility, interaction, responsive layout, typography, color, charts, and stack-specific UI implementation. Searchable local data: 79 searchable styles (50 active), 192 product palettes and reasoning profiles, 74 font pairings, 119 UX guidelines, 105 icons, 17 GSAP presets, 25 chart types, and 22 stacks.
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Extracts structured data from LLM responses using JSON schemas, Zod validation, and function calling for reliable parsing. Use when users request "structured output", "JSON extraction", "parse LLM response", "function calling", or "typed responses".
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Standardizes UX states for data fetching flows (loading, error, empty, success) and complex multi-view UI patterns. Provides state machine approach recommendations, loading skeletons, error boundaries, and empty state components. Use when implementing "loading states", "error handling", "empty states", or "state machines".
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Defines measurable performance budgets for bundle size, API latency, database queries, and render times. Provides enforcement strategies and monitoring plans. Use for "performance budgets", "performance monitoring", "web vitals", or "optimization targets".
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Designs retrieval-augmented generation pipelines for document-based AI assistants. Includes chunking strategies, metadata schemas, retrieval algorithms, reranking, and evaluation plans. Use when building "RAG systems", "document search", "semantic search", or "knowledge bases".
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Implements React Server Components (RSC) patterns with Next.js App Router including data fetching, streaming, selective hydration, and server/client composition. Use when users request "server components", "RSC", "Next.js app router", "server-side rendering", or "streaming".
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Creates custom React hooks for common patterns including data fetching, forms, authentication, local storage, debounce, and more. Use when users request "create custom hook", "React hook for", "useX hook", or "reusable hook".
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Migrates REST APIs to GraphQL incrementally with schema stitching, REST datasources, and gradual endpoint migration. Use when users request "migrate to GraphQL", "REST to GraphQL", "GraphQL wrapper", or "API modernization".
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Builds end-to-end browser tests for critical user flows using Playwright or Cypress. Includes selector strategies, test data management, page objects, and visual regression testing. Use for "E2E testing", "browser tests", "Playwright", or "Cypress tests".
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Raw mechanical interfaces fusing Swiss typographic print with military terminal aesthetics. Rigid grids, extreme type scale contrast, utilitarian color, analog degradation effects. For data-heavy dashboards, portfolios, or editorial sites that need to feel like declassified blueprints.
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Builds repeatable evaluation systems with golden datasets, scoring rubrics, pass/fail thresholds, and regression reports. Use for "LLM evaluation", "testing AI systems", "quality assurance", or "model benchmarking".
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Produces build artifacts with Software Bill of Materials (SBOM) and supply chain metadata for security and compliance. Use for "artifact publishing", "SBOM generation", "supply chain security", or "build provenance".
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Scans repository structure and generates comprehensive architecture documentation including system overview, entry points, module relationships, data flow diagrams, and "edit here for X" guides. Creates ARCHITECTURE.md for onboarding and navigation. Use when users request "document the codebase", "explain the architecture", "create onboarding docs", or "map the system".
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Use when AI contribution metadata must match the actual workflow, when model alias and dated identifiers need auditing, when verified and fabricated citation counts feed a release decision, or when a venue's AI disclosure statement needs evidence behind it.
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Use when selecting a statistical test with AI consultation, when assumptions need checking against the actual data, when an analysis plan or decision log must be written before running anything, or when results need APA-style reporting with effect sizes.
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