Total 57,184 skills, AI & Machine Learning has 9512 skills
Showing 12 of 9512 skills
Meta-skill for analyzing PRs, issues, and user interactions to improve Cursor rules and skills automatically
PyTorch deep learning development with transformers, diffusion models, and GPU optimization.
Enable agents to use the Clawhub CLI (clawbub) to install, import, publish, and manage AgentSkills. Use when an agent needs to interact with Clawhub from the command line for skill development, publishing, or syncing.
Agent skill for load-balancer - invoke with $agent-load-balancer
Transform extracted engineer expertise into an actionable skill with progressive disclosure, allowing agents to find and apply relevant patterns for specific tasks.
Vision framework API, VNDetectHumanHandPoseRequest, VNDetectHumanBodyPoseRequest, person segmentation, face detection, VNImageRequestHandler, recognized points, joint landmarks, VNRecognizeTextRequest, VNDetectBarcodesRequest, DataScannerViewController, VNDocumentCameraViewController, RecognizeDocumentsRequest
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
Advanced sub-skill for PyTorch focused on deep research and production engineering. Covers custom Autograd functions, module hooks, advanced initialization, Distributed Data Parallel (DDP), and performance profiling.
xAI Grok API authentication and setup. Use when configuring xAI API access, setting up API keys, or troubleshooting authentication issues.
OpenAI API via curl. Use this skill for GPT chat completions, DALL-E image generation, Whisper audio transcription, embeddings, and text-to-speech.
Score, grade, or evaluate things using AI against a rubric. Use when grading essays, scoring code reviews, rating candidate responses, auditing support quality, evaluating compliance, building a quality rubric, running QA checks against criteria, assessing performance, rating content quality, or any task where you need numeric scores with justifications — not just categories.
Scaffold a new AI feature powered by DSPy. Use when adding AI to your app, starting a new AI project, building an AI-powered feature, setting up a DSPy program from scratch, or bootstrapping an LLM-powered backend.