Loading...
Loading...
Found 2,097 Skills
Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.
Review the latest changes and check whether they comply with the project's documented guidelines (AGENTS.md, CLAUDE.md, or equivalent). Use when reviewing local diffs, recent commits, or feature work and you need a findings-first assessment of architecture, reuse, testing, and repo-specific rules.
Query AI coding agent usage, costs, and token consumption. Supports Claude Code, Codex CLI, OpenClaw, and OpenCode. Ask about spending, token usage, model costs, session history, API call counts. Actions: check usage, show cost, compare models, list sessions, analyze spending, token breakdown. Time ranges: today, this week, this month, this year, last N days, custom dates.
Build RAG pipelines with Exa.ai for real-time web retrieval. Use when building retrieval-augmented generation, integrating Exa with LangChain, LlamaIndex, Vercel AI SDK, or implementing AI agents with web search capabilities. Triggers on: RAG pipeline, retrieval augmented generation, Exa LangChain, Exa LlamaIndex, ExaSearchRetriever, ExaSearchResults, Exa MCP, Exa tool calling, Claude tool use, AI agent web search, grounded generation, citation generation, fact checking, hallucination detection, OpenAI compatibility, chat completions.
Use when user needs capabilities Claude lacks (image generation, real-time X/Twitter data) or explicitly requests external models ("blockrun", "use grok", "use gpt", "dall-e", "deepseek")
Presentation creation, editing, and analysis. Used when Claude needs to handle presentation files (.pptx), including: (1) creating new presentations, (2) modifying or editing content, (3) handling layouts, (4) adding comments or speaker notes, or any other presentation-related tasks
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
Automatically sync Agents.md, claude.md and gemini.md files in the project to maintain content consistency. Supports automatic monitoring and manual triggering.
Amazon Bedrock Model Customization with fine-tuning, continued pre-training, reinforcement fine-tuning (NEW 2025 - 66% accuracy gains), and distillation. Create customization jobs, monitor training, deploy custom models, and evaluate performance. Use when customizing Claude, Titan, or other Bedrock models for domain-specific tasks, adapting to proprietary data, improving accuracy on specialized workflows, or distilling large models to smaller ones.
Securely manages API credentials for multiple providers (Anthropic Claude, Google Gemini, GitHub). Use when skills need to access stored API keys for external service invocations.
Interactive conversation to resolve [NEEDS CLARIFICATION] markers using /speckit.clarify command. Claude asks questions about missing features, UX/UI details, behavior, and priorities. Updates specs in .specify/memory/ with answers to create complete, unambiguous documentation. This is Step 5 of 6 in the reverse engineering process.
Integrate TheSys C1 Generative UI API to stream interactive React components (forms, charts, tables) from LLM responses. Supports Vite+React, Next.js, and Cloudflare Workers with OpenAI, Anthropic Claude, and Workers AI. Use when building conversational UIs, AI assistants with rich interactions, or troubleshooting empty responses, theme application failures, streaming issues, or tool calling errors.