Skills
98,067 packaged capabilities and playbooks for agents. Install any of them with one command.
Development
Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API integration, database operations, AI agent workflows, or scheduled tasks.
Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.
Node.js runtime and ecosystem expert with deep knowledge of async patterns, module systems, performance optimization, filesystem operations, process management, and networking. Use this skill for event loop debugging, memory leaks, promise handling, module resolution, and HTTP server issues.
Use when an idea needs disciplined exploration before building: generate options, test whether it is worth building, map adjacent solutions, challenge assumptions, narrow scope, or choose Build RFC / Prototype / Narrow / Park — even if nobody said brainstorm. Already decided to implement a specific plan → skip.
Build agentic AI applications with OpenAI's Responses API - the stateful successor to Chat Completions. Preserves reasoning across turns for 5% better multi-turn performance and 40-80% improved cache utilization. Use when: building AI agents with persistent reasoning, integrating MCP servers for external tools, using built-in Code Interpreter/File Search/Web Search, managing stateful conversations, implementing background processing for long tasks, or migrating from Chat Completions to gain polymorphic outputs and server-side tools.
GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster. Use for CUDA/GPU optimization; CPU-bound NumPy, SciPy, pandas, scikit-learn, NetworkX, scikit-image, vector-search, image-processing, graph, simulation, or file-I/O workloads; CuPy, cuDF, cuML, cuGraph, cuVS, cuCIM, KvikIO, Warp, Newton, Numba-CUDA, or RAFT questions; and profiling, memory-transfer, kernel, or multi-GPU bottlenecks. Also use when large data-parallel Python code is slow and GPU acceleration is a plausible option, even if the user does not name CUDA.
This skill should be used when the user asks to "optimize images", "compress images", "reduce image file size", "make images smaller", "optimize PNGs", "optimize JPEGs", "speed up website images", "reduce bundle size images", or needs help with image compression for web projects. Provides workflows and scripts for batch image optimization using sharp.
Operate Orca-managed worktrees, folder contexts, terminals, repos, automations, artifacts, skill sharing, worktree comments, and Orca's embedded browser through the `orca` CLI. Use when the user says "$orca-cli", "Orca worktree", "child worktree", "spawn codex/claude in a worktree", "read/wait/send Orca terminal", "handoff" / "handover" / "give this to another agent", "Orca browser", "orca artifacts", or "share skills". Prefer it over raw git worktree, ad hoc PTYs, or Computer Use when Orca state is involved. Use Computer Use only when a visible window needs GUI control that a CLI, filesystem, or API cannot do.
Coordinate an end-to-end Jira or GitHub work-item workflow from initial fetch through per-task implementation. Use this skill when the user provides a Jira ticket URL, a GitHub issue URL, owner/repo/issue coordinates, says "work on ticket PROJECT-123", "work on issue owner/repo#42", "resume <work-item-key>", "continue this workflow", or asks for status without naming a specific phase. This top-level coordinator detects the platform from the input, loads the matching playbook just-in-time, keeps SKILL.md as a routing layer, and dispatches execution-heavy work to downstream skills or co-located utility subagents.
Use when contributing code to an existing project - guarantees that every new line mirrors the established conventions, naming schemes, architectural layering, directory layout, and stylistic choices already present in the codebase rather than drifting toward generic AI defaults
Spatial indexing and world streaming for Three.js building games with thousands of pieces. Use when optimizing building games, implementing spatial queries, chunk loading, or profiling performance. Includes spatial hash grids, octrees, chunk managers, and benchmarking tools.
Identifies and fixes Rails performance issues including N+1 queries, slow queries, and memory problems. Use when optimizing queries, fixing N+1 issues, improving response times, or when user mentions performance, slow, optimization, or Bullet gem. WHEN NOT: Caching-specific patterns (use caching-strategies), adding new features, or general code quality improvements unrelated to speed.
Guide performance profiling for Apple platform apps with Instruments, Xcode diagnostics, and MetricKit. Use when investigating app hangs, stutters, high CPU, memory leaks, memory growth, OOM crashes, slow launch, battery drain, thermal issues, App Store performance readiness, or when adding os_signpost and measurement hooks
Playdate game development in Lua with the Playdate SDK. Covers game loop, sprites, graphics, input (crank, buttons, accelerometer), audio, UI, performance, metadata (pdxinfo), and simulator/device workflow. Use when asked to make a Playdate game, implement Playdate-specific mechanics, or apply Playdate design and accessibility guidelines.
Pre-commit hooks framework for multi-language code quality automation. USE WHEN setting up pre-commit OR configuring git hooks OR adding linting OR code formatting OR security scanning OR Terraform validation OR Kubernetes manifests OR Helm charts OR Python linting OR JavaScript formatting. Manages .pre-commit-config.yaml, hook installation, and CI integration.
Onboard prek (Rust-powered pre-commit) into any project and suggest hooks tailored to the language/framework. Use when the user says "add prek", "set up pre-commit hooks", "configure prek", "what hooks should I use", or when you notice a project without a prek.toml that would benefit from pre-commit checks. Also trigger when the user wants to add new hooks to an existing prek.toml, audit their hook config, or migrate from pre-commit to prek. Covers Rust, Python, TypeScript/JavaScript, Go, Ruby, and Shell projects. Do NOT use for husky, lint-staged, or CI pipeline hook configuration — this skill is specifically for prek.
Project planning and feature breakdown for Python/React full-stack projects. Use during the planning phase when breaking down feature requests, user stories, or product requirements into implementation plans. Guides identification of affected files and modules, defines acceptance criteria, assesses risks, and estimates overall complexity. Produces module maps, risk assessments, and acceptance criteria. Does NOT cover architecture decisions (use system-architecture), implementation (use python-backend-expert or react-frontend-expert), or atomic task decomposition (use task-decomposition).
Generate structured planning documentation for web projects with context-safe phases, verification criteria, and exit conditions. Creates IMPLEMENTATION_PHASES.md plus conditional docs (DATABASE_SCHEMA, API_ENDPOINTS, UI_COMPONENTS, CRITICAL_WORKFLOWS). Use when: starting new Cloudflare Workers/React projects, adding major features to existing apps, breaking large work into manageable phases, or need verified planning before coding begins.
Real-time presence with PubNub. Covers Admin Portal Presence add-on configuration, join/leave/timeout events, hereNow occupancy, presence state, dropped-connection categories (PNNetworkDownCategory etc.), heartbeat tuning, and multi-device sync for the same userId. Use when implementing online/offline indicators, occupancy counts, last-seen tracking, or troubleshooting presence flapping.
Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
Blockchain RPC and data access via Quicknode. Use when an agent needs to read onchain data (balances, token prices, transaction status, gas estimates, block data) across Base, Ethereum, Polygon, Solana, or Unichain. Supports both API key access and x402 wallet-based pay-per-request access with no account needed. Triggers on mentions of RPC, blockchain data, onchain queries, token balances, gas estimation, block number, transaction receipt, Quicknode, or x402.
Use when adding or reviewing background jobs in Rails. Configures Active Job workers, implements idempotency checks, sets up retry/discard strategies, selects Solid Queue (Rails 8+) or Sidekiq based on scale, and defines recurring jobs via recurring.yml or sidekiq-cron. Trigger words: background job, Active Job, Solid Queue, Sidekiq, idempotency, retry, discard, recurring job, queue.
Reviews Rails pull requests, focusing on controller/model conventions, migration safety, query performance, and Rails Way compliance. Covers routing, ActiveRecord, security, caching, and background jobs. Use when reviewing existing Rails code for quality, conducting a PR review, or doing a code review on Ruby on Rails (RoR) code.
Analyzes Rails applications and generates comprehensive upgrade reports with breaking changes, deprecations, and step-by-step migration guides for Rails 2.3 through 8.1. Use when upgrading Rails applications, planning multi-hop upgrades, querying version-specific changes, or answering what stands between the app and the next Rails version. Based on FastRuby.io methodology and "The Complete Guide to Upgrade Rails" ebook.
Unified handling of address space conversion: determining PIE/ASLR base addresses, RVA/VA conversion, loader offset (firmware load address vs link address), cross-tool address alignment (Ghidra/angr/frida/gdb). Triggers: PIE, ASLR, base address, RVA, VA, loader offset, address conversion, relocated address, computing addresses in gdb, angr addresses.
React 19 new features and APIs. Covers Actions, useActionState, useFormStatus, useOptimistic, use() hook, Server Components, Server Actions, improved ref handling, document metadata, and new compiler. USE WHEN: user mentions "React 19", "useActionState", "useFormStatus", "useOptimistic", "use() hook", "Server Components", "Server Actions", "React Compiler", asks about "React 19 features", "Actions in React", "ref as prop" DO NOT USE FOR: React 18 and earlier - use `react` skill instead, forms in general - use `react-forms` or `react-hook-form` skills instead
React hooks best practices for React application code and custom hook design across DX, optimization, and logic. Use when writing components with hooks, creating or refactoring custom hooks, reviewing hook usage/APIs/internals, checking effects/dependencies/state/refs/callbacks, or improving hook correctness, ergonomics, and performance.
React 19 patterns and React Compiler behavior with Context shorthand syntax and use() hook. Use when working with Context, useContext, use() hook, Provider components, optimization patterns like useMemo, useCallback, memo, memoization, or when the user mentions React 19, React Compiler, Context.Provider, or manual optimization.
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.