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Found 9,585 Skills
This skill should be used when the user asks to refactor specific files or directories, simplify recently changed code, clean up dead code in a limited scope, or invokes `/refactor` with paths or semantic queries.
Master of stylized atmospheric effects using SVG filters and CSS animations. Creates clouds, waves, lightning, rain, fog, aurora borealis, god rays, lens flares, twilight skies, and ocean spray—all with a premium aesthetic that's stylized but never cheap-looking.
Production-tested setup for Zustand state management in React applications with TypeScript. This skill provides comprehensive patterns for building scalable, type-safe global state. Use when: setting up global state in React, migrating from Redux or Context API, implementing state persistence with localStorage, configuring TypeScript with Zustand, using slices pattern for modular stores, adding devtools middleware for debugging, handling Next.js SSR hydration, or encountering hydration errors, TypeScript inference issues, or persist middleware problems. Prevents 5 documented issues: Next.js hydration mismatches, TypeScript double parentheses syntax errors, persist middleware export errors, infinite render loops, and slices pattern type inference failures. Keywords: zustand, state management, React state, TypeScript state, persist middleware, devtools, slices pattern, global state, React hooks, create store, useBoundStore, StateCreator, hydration error, text content mismatch, infinite render, localStorage, sessionStorage, immer middleware, shallow equality, selector pattern, zustand v5
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Numerical algorithms and computational techniques for statistics
Complete knowledge domain for Cloudflare Workers AI - Run AI models on serverless GPUs across Cloudflare's global network. Use when: implementing AI inference on Workers, running LLM models, generating text/images with AI, configuring Workers AI bindings, implementing AI streaming, using AI Gateway, integrating with embeddings/RAG systems, or encountering "AI_ERROR", rate limit errors, model not found, token limit exceeded, or neurons exceeded errors. Keywords: workers ai, cloudflare ai, ai bindings, llm workers, @cf/meta/llama, workers ai models, ai inference, cloudflare llm, ai streaming, text generation ai, ai embeddings, image generation ai, workers ai rag, ai gateway, llama workers, flux image generation, stable diffusion workers, vision models ai, ai chat completion, AI_ERROR, rate limit ai, model not found, token limit exceeded, neurons exceeded, ai quota exceeded, streaming failed, model unavailable, workers ai hono, ai gateway workers, vercel ai sdk workers, openai compatible workers, workers ai vectorize
Sets up Python development environment using UV for fast dependency management. Configures virtual environment, dependencies, testing (pytest), linting/formatting (ruff), and type checking (mypy). ALWAYS use UV - NEVER use pip directly. Use when starting work on Python projects, after cloning Python repositories, setting up CI/CD for Python, or troubleshooting Python environment issues.
Before ANY significant development task (new feature, refactor, integration, migration), run a complete planning ritual by orchestrating other skills in sequence: rubber-duck (clarify scope) -> pre-mortem (assess risks) -> eta (estimate time) -> final confirmation. Do not start coding until the battle plan is approved.
Transform project briefs into testable specifications with acceptance criteria. Use for requirements translation, spec creation, pre-implementation. Skip if spec exists or still exploring.
Best practices for managing development environments including Python venv and conda. Always check environment status before installations and confirm with user before proceeding.
Universal ChromaDB integration patterns for semantic search, persistent storage, and pattern matching across all agent types. Use when agents need to store/search large datasets, build knowledge bases, perform semantic analysis, or maintain persistent memory across sessions.
Agent Context Isolation