Total 30,711 skills, AI & Machine Learning has 4960 skills
Showing 12 of 4960 skills
Set up automated agent-driven development with Ralph. Run AI agents in a loop to implement features from user stories, verify acceptance criteria, and log progress for the next agent.
Install the Vercel AI SDK with AI Elements components. Build a streaming chat interface with the useChat hook.
Design and build AI agents for any domain. Use when users: (1) ask to "create an agent", "build an assistant", or "design an AI system" (2) want to understand agent architecture, agentic patterns, or autonomous AI (3) need help with capabilities, subagents, planning, or skill mechanisms (4) ask about Claude Code, Cursor, or similar agent internals (5) want to build agents for business, research, creative, or operational tasks Keywords: agent, assistant, autonomous, workflow, tool use, multi-step, orchestration
Persist AI chat conversations to Neon Postgres with full support for AI SDK message parts including tools, reasoning, and streaming. Uses UUID v7 for chronologically-sortable IDs.
Configure AI coding agents like Cursor, GitHub Copilot, or Claude Code with project-specific patterns, coding guidelines, and MCP servers for consistent AI-assisted development.
Build a custom durable AI agent with full control over streamText options, provider configs, and tool loops. Compatible with the Workflow Development Kit.
Use when user needs ML model deployment, production serving infrastructure, optimization strategies, and real-time inference systems. Designs and implements scalable ML systems with focus on reliability and performance.
Converting markdown plans into beads (tasks with dependencies) and polishing them until they're implementation-ready. The bridge between planning and agent swarm execution. Includes exact prompts used.
Create event-driven hooks for Claude Code automation. Configure hook events in settings or frontmatter, parse stdin JSON inputs, return decision-control JSON, and implement secure hook scripts.
Use when implementing on-device AI with Apple's Foundation Models framework — prevents context overflow, blocking UI, wrong model use cases, and manual JSON parsing when @Generable should be used. iOS 26+, macOS 26+, iPadOS 26+, axiom-visionOS 26+
Design tools that agents can use effectively, including when to reduce tool complexity. Use when creating, optimizing, or reducing agent tool sets.
MCP (Model Context Protocol) server building principles. Tool design, resource patterns, best practices.