Skills
The open registry for AI agent skills — structured prompts and workflows with recommended models, example prompts, and compatible tools.
Skills
37
Categories
9
Compatible tools
6
Contributors
1
Showing 1–21 of 37 skills
Designs caching strategies across the stack to cut latency and load. Chooses cache layers (browser, CDN, application, database), picks patterns (cache-aside, read-through, write-through, write-behind), sets TTLs and eviction policies, and plans invalidation to avoid staleness and stampedes. Produces a layered plan with keys, TTLs, and invalidation rules.
Sets up and maintains Git hooks for a repository. Recommends a manager (Husky, Lefthook, or pre-commit), wires up pre-commit and commit-msg hooks for linting, formatting, type checks, secret scanning, and conventional-commit validation, and keeps hooks fast with staged-file filtering. Produces config plus a short contributor guide.
Designs and implements rate limiting for APIs and services. Recommends an algorithm (token bucket, leaky bucket, fixed or sliding window) for the use case, defines per-key and per-endpoint limits, plans distributed enforcement with Redis, and specifies response headers and 429 handling with retry-after. Produces a design plus reference implementation.
Analyzes LLM usage and reduces inference cost without sacrificing quality. Covers prompt compression, context trimming, caching (prompt and semantic), model routing by task difficulty, batching, structured output to cut retries, and token accounting. Produces a concrete plan with estimated savings and quality guardrails.
Designs and scaffolds ergonomic command-line tools with subcommands, flags, config files, shell completions, and helpful error output. Covers argument parsing conventions, exit codes, stdin/stdout piping, colored output, progress indicators, and cross-platform packaging. Produces maintainable CLIs that follow POSIX conventions and feel great to use.
Implements secure OAuth 2.0 and OpenID Connect flows including authorization code with PKCE, client credentials, and device code grants. Generates token exchange logic, refresh handling, state/nonce validation, and secure token storage. Flags common pitfalls like implicit flow usage, missing PKCE, and insecure redirect URI handling.
Designs routing layers that dispatch requests across multiple LLMs based on task type, difficulty, latency, cost, and reliability. Covers classifier-based and heuristic routing, fallbacks and retries across providers, quality scoring, and A/B evaluation of routing policies. Helps teams get frontier quality where it matters and cheap models everywhere else.
Builds robust webhook producers and consumers. Covers signature verification, idempotency keys, retry with exponential backoff, dead-letter handling, event ordering, and replay endpoints, and generates handler code plus tests so integrations survive duplicates and outages.
Builds cross-browser extensions on Manifest V3 with background service workers, content scripts, popup and options UIs, and message passing. Covers permissions scoping, storage sync, context menus, and store submission requirements for Chrome, Edge, and Firefox. Emphasizes least-privilege permissions and secure content-script isolation.
Advises on how to evolve APIs without breaking clients. Compares versioning strategies (URI, header, media-type), classifies changes as breaking or non-breaking, and produces deprecation timelines, migration guides, and compatibility shims so teams can ship changes safely.
Models complex application logic as explicit finite state machines and statecharts. Identifies states, events, guards, and side effects; prevents impossible states; and generates implementations (e.g., XState-style) with diagrams. Ideal for wizards, checkout flows, connection lifecycles, and any feature where implicit boolean flags cause bugs.
Designs and implements real-time services using WebSockets and Server-Sent Events. Covers connection lifecycle, heartbeats, reconnection with backoff, room/channel fan-out, backpressure, authentication on upgrade, and horizontal scaling with a pub/sub backplane. Produces production patterns for chat, live dashboards, collaborative editing, and streaming updates.
Modernizes legacy codebases incrementally and safely. Establishes characterization tests to lock in current behavior, then applies the strangler-fig pattern, dependency updates, and idiomatic refactors in small verifiable steps, producing a migration plan that avoids big-bang rewrites.
Designs multi-agent systems where a coordinator delegates sub-tasks to specialist agents, verifies intermediate results, and synthesizes a final answer. Covers agent role definition, routing and delegation strategy, shared memory and message passing, verification loops, cost and latency budgeting, and failure handling across frameworks like LangGraph, CrewAI, or a custom orchestrator.
Plans and executes safe dependency upgrades across a project. Analyzes current versions, reads changelogs and release notes for breaking changes, sequences upgrades to minimize risk, applies required code migrations, and verifies with builds and tests. Works across npm, pip, Maven, Cargo, and Go modules.
Writes safe, reversible database schema migrations and the corresponding rollback scripts. Plans zero-downtime changes using expand-and-contract patterns, handles data backfills and index creation without locking, and generates migrations for tools like Alembic, Flyway, Prisma, Knex, and Rails ActiveRecord with clear up/down steps.
Adds clear, accurate inline comments and API doc blocks to existing code without changing behavior. Generates docstrings and structured comments (JSDoc, Google/NumPy style, Javadoc, Rustdoc) that explain intent, parameters, return values, side effects, and edge cases, while avoiding noisy comments that merely restate the code.
Designs GraphQL schemas from domain descriptions or existing data models. Produces typed SDL with queries, mutations, subscriptions, input types, enums, and interfaces, following naming conventions, pagination patterns (Relay-style connections), and error-handling best practices. Can also generate resolvers scaffolding and map schemas to existing REST or SQL backends.
Generates mobile application prototypes and implementations for iOS and Android. Creates SwiftUI views, Jetpack Compose layouts, and React Native components from descriptions or wireframe images. Handles navigation patterns, state management, and platform-specific design guidelines.
Interacts with GitHub via the gh CLI for managing issues, pull requests, CI runs, releases, and repository settings. Automates common GitHub workflows including PR creation with proper descriptions, issue triage, release drafting, and CI debugging.
Designs and scaffolds AI agent architectures including tool definitions, system prompts, memory strategies, and orchestration logic. Supports multi-agent workflows, ReAct patterns, function calling schemas, and MCP server configurations. Helps structure agents that are reliable, observable, and easy to debug.
Skills vs MCP servers
what's the difference?Skillsthe “what to do”
A skillA reusable, structured prompt/workflow with recommended models, an example prompt, and compatible tools. packages know-how — instructions, an example promptA ready-to-use prompt template that demonstrates how to invoke the skill., and recommended models — so an agent performs a task consistently. Skills add knowledge, not new connections.
MCP serversthe “how to connect”
An MCP serverModel Context Protocol server — a standard way to expose tools, resources, and prompts to AI agents and IDEs. gives an agent new capabilities by connecting it to real systems (databases, APIs, files) over a transportHow the client talks to the server: stdio (local process), SSE, or HTTP streaming.. MCP adds connections and actions, not task instructions.
Rule of thumb: reach for a skill when you need the model to do a task well, and an MCP server when you need it to reach a tool or system. They compose — a skill can rely on tools an MCP server provides.
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