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Found 1,576 Skills
Interact with Google's Gemini model via CLI. Use when needing a second opinion from another LLM, cross-validation, or leveraging Gemini's Google Search grounding. Supports multi-turn conversations with session management.
Execute Gemini CLI for AI-powered code analysis and generation. Use when you need to leverage Google's Gemini models for complex reasoning tasks.
Analyze debt covenants and credit agreement terms from SEC filings using Octagon MCP. Use when researching financial covenants, leverage ratios, interest coverage requirements, credit facilities, debt maturity schedules, and covenant compliance from 10-K, 10-Q, and 8-K filings.
Retrieve detailed balance sheet statement data including Total Assets, Current Assets, Non-Current Assets, Liabilities, Equity, and Net Debt for public companies. Use when analyzing financial position, capital structure, or leverage metrics.
Retrieve a daily overview of industry performance using Octagon MCP. Use when analyzing daily price movements, average changes, and performance trends for specific industries within an exchange.
Retrieve industry-specific P/E ratios using Octagon MCP. Use when comparing company valuations to specific industry peers, analyzing sub-sector valuations, and understanding niche market valuations beyond broad sector averages.
High-performance Rust web crawler with stealth mode, LLM-ready Markdown export, multi-format output, sitemap discovery, and robots.txt support. Optimized for content extraction, site mapping, structure analysis, and LLM/RAG pipelines.
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
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
Complete guide for OpenAI's Assistants API v2: stateful conversational AI with built-in tools (Code Interpreter, File Search, Function Calling), vector stores for RAG (up to 10,000 files), thread/run lifecycle management, and streaming patterns. Both Node.js SDK and fetch approaches. ⚠️ DEPRECATION NOTICE: OpenAI plans to sunset Assistants API in H1 2026 in favor of Responses API. This skill remains valuable for existing apps and migration planning. Use when: building stateful chatbots with OpenAI, implementing RAG with vector stores, executing Python code with Code Interpreter, using file search for document Q&A, managing conversation threads, streaming assistant responses, or encountering errors like "thread already has active run", vector store indexing delays, run polling timeouts, or file upload issues. Keywords: openai assistants, assistants api, openai threads, openai runs, code interpreter assistant, file search openai, vector store openai, openai rag, assistant streaming, thread persistence, stateful chatbot, thread already has active run, run status polling, vector store error
Comprehensive guide for Cloudflare Durable Objects - globally unique, stateful objects for coordination, real-time communication, and persistent state management. Use when: building real-time applications, creating WebSocket servers with hibernation, implementing chat rooms or multiplayer games, coordinating between multiple clients, managing per-user or per-room state, implementing rate limiting or session management, scheduling tasks with alarms, building queues or workflows, or encountering "do class export", "new_sqlite_classes", "migrations required", "websocket hibernation", "alarm api error", or "global uniqueness" errors. Prevents 15+ documented issues: class not exported, missing migrations, wrong migration type, constructor overhead blocking hibernation, setTimeout breaking hibernation, in-memory state lost on hibernation, outgoing WebSocket not hibernating, global uniqueness confusion, partial deleteAll on KV backend, binding name mismatches, state size limits exceeded, non-atomic migrations, location hints misunderstood, alarm retry failures, and fetch calls blocking hibernation. Keywords: durable objects, cloudflare do, DurableObject class, do bindings, websocket hibernation, do state api, ctx.storage.sql, ctx.acceptWebSocket, webSocketMessage, alarm() handler, storage.setAlarm, idFromName, newUniqueId, getByName, DurableObjectStub, serializeAttachment, real-time cloudflare, multiplayer cloudflare, chat room workers, coordination cloudflare, stateful workers, new_sqlite_classes, do migrations, location hints, RPC methods, blockConcurrencyWhile, "do class export", "new_sqlite_classes", "migrations required", "websocket hibernation", "alarm api error", "global uniqueness", "binding not found"
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