Total 39,544 skills
Showing 12 of 39544 skills
This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle
Securely authenticate with GitHub using stored credentials for API operations and git commands
This skill provides comprehensive knowledge for building applications with Cloudflare Sandboxes SDK, which enables secure, isolated code execution in full Linux containers at the edge. It should be used when executing untrusted code, running Python/Node.js scripts, performing git operations, building AI code execution systems, creating interactive development environments, or implementing CI/CD workflows that require full OS capabilities. Use when: Setting up Cloudflare Sandboxes, executing Python/Node.js code safely, managing stateful development environments, implementing AI code interpreters, running shell commands in isolation, handling git repositories programmatically, building chat-based coding agents, creating temporary build environments, processing files with system tools (ffmpeg, imagemagick, etc.), or when encountering issues with container lifecycle, session management, or state persistence. Keywords: cloudflare sandbox, container execution, code execution, isolated environment, durable objects, linux container, python execution, node execution, git operations, code interpreter, AI agents, session management, ephemeral container, workspace, sandbox SDK, @cloudflare/sandbox, exec(), getSandbox(), runCode(), gitCheckout(), ubuntu container
Use this skill when building AI applications with OpenAI Agents SDK for JavaScript/TypeScript. The skill covers both text-based agents and realtime voice agents, including multi-agent workflows (handoffs), tools with Zod schemas, input/output guardrails, structured outputs, streaming, human-in-the-loop patterns, and framework integrations for Cloudflare Workers, Next.js, and React. It prevents 9+ common errors including Zod schema type errors, MCP tracing failures, infinite loops, tool call failures, and schema mismatches. The skill includes comprehensive templates for all agent types, error handling patterns, and debugging strategies. Keywords: OpenAI Agents SDK, @openai/agents, @openai/agents-realtime, openai agents javascript, openai agents typescript, text agents, voice agents, realtime agents, multi-agent workflows, agent handoffs, agent tools, zod schemas agents, structured outputs agents, agent streaming, agent guardrails, input guardrails, output guardrails, human-in-the-loop, cloudflare workers agents, nextjs openai agents, react openai agents, hono agents, agent debugging, Zod schema type error, MCP tracing failure, agent infinite loop, tool call failures, schema mismatch agents
Use this skill when building MCP (Model Context Protocol) servers with FastMCP in Python. FastMCP is a framework for creating servers that expose tools, resources, and prompts to LLMs like Claude. The skill covers server creation, tool/resource definitions, storage backends (memory/disk/Redis/DynamoDB), server lifespans, middleware system (8 built-in types), server composition (import/mount), OAuth Proxy, authentication patterns, icons, OpenAPI integration, client configuration, cloud deployment (FastMCP Cloud), error handling, and production patterns. It prevents 25+ common errors including storage misconfiguration, lifespan issues, middleware order errors, circular imports, module-level server issues, async/await confusion, OAuth security vulnerabilities, and cloud deployment failures. Includes templates for basic servers, storage backends, middleware, server composition, OAuth proxy, API integrations, testing, and self-contained production architectures. Keywords: FastMCP, MCP server Python, Model Context Protocol Python, fastmcp framework, mcp tools, mcp resources, mcp prompts, fastmcp storage, fastmcp memory storage, fastmcp disk storage, fastmcp redis, fastmcp dynamodb, fastmcp lifespan, fastmcp middleware, fastmcp oauth proxy, server composition mcp, fastmcp import, fastmcp mount, fastmcp cloud, fastmcp deployment, mcp authentication, fastmcp icons, openapi mcp, claude mcp server, fastmcp testing, storage misconfiguration, lifespan issues, middleware order, circular imports, module-level server, async await mcp
Creates complete single-file HTML/CSS/JS web apps with localStorage persistence, ADHD-optimized UI (60px+ buttons), dark mode, and offline functionality. Use when user says "create app", "build tool", "make dashboard", or requests any browser-based interface.
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
Executes OpenAI Codex CLI for code analysis, refactoring, and automated editing. Activates when users mention codex commands, code review requests, or automated code transformations requiring advanced reasoning models.
Backend AI functionality with Vercel AI SDK v5 - text generation, structured output with Zod, tool calling, and agents. Multi-provider support for OpenAI, Anthropic, Google, and Cloudflare Workers AI. Use when: implementing server-side AI features, generating text/chat completions, creating structured AI outputs with Zod schemas, building AI agents with tools, streaming AI responses, integrating OpenAI/Anthropic/Google/Cloudflare providers, or encountering AI SDK errors like AI_APICallError, AI_NoObjectGeneratedError, streaming failures, or worker startup limits. Keywords: ai sdk core, vercel ai sdk, generateText, streamText, generateObject, streamObject, ai sdk node, ai sdk server, zod ai schema, ai tools calling, ai agent class, openai sdk, anthropic sdk, google gemini sdk, workers-ai-provider, ai streaming backend, multi-provider ai, ai sdk errors, AI_APICallError, AI_NoObjectGeneratedError, streamText fails, worker startup limit ai
Transform infrastructure documentation, runbooks, and operational knowledge into reusable Claude Code skills. Convert Proxmox configs, Docker setups, Kubernetes deployments, and cloud infrastructure patterns into structured, actionable skills.
Expert helper for bash scripting, debugging, and best practices
This skill provides comprehensive knowledge for integrating Vercel KV (Redis-compatible key-value storage powered by Upstash) into Vercel applications. It should be used when setting up Vercel KV for Next.js applications, implementing caching patterns, managing sessions, or handling rate limiting in edge and serverless functions. Use this skill when: - Setting up Vercel KV for Next.js applications - Implementing caching strategies (page cache, API cache, data cache) - Managing user sessions or authentication tokens in serverless environments - Building rate limiting for APIs or features - Storing temporary data with TTL (time-to-live) - Migrating from Cloudflare KV to Vercel KV - Encountering errors like "KV_REST_API_URL not set", "rate limit exceeded", or "JSON serialization errors" - Need Redis-compatible API with strong consistency (vs eventual consistency) Keywords: vercel kv, @vercel/kv, vercel redis, upstash vercel, kv vercel, redis vercel edge, key-value vercel, vercel cache, vercel sessions, vercel rate limit, redis upstash, kv storage, edge kv, serverless redis, vercel ttl, vercel expire, kv typescript, next.js kv, server actions kv, edge runtime kv