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Found 5 Skills
Build AI agent UIs using the AG-UI protocol with pydantic-ai (Python backend) and CopilotKit (React frontend). Use when creating agentic chat interfaces, human-in-the-loop workflows, generative UIs with state management, tool-based rendering, shared state between frontend and backend, or predictive state updates. Covers FastAPI integration, state events (StateSnapshotEvent, StateDeltaEvent, CustomEvent), useCoAgent hooks, useCopilotAction for tool rendering, and real-time agent-frontend synchronization.
Integration patterns for Mapbox MCP Server in AI applications and agent frameworks. Covers runtime integration with pydantic-ai, mastra, LangChain, and custom agents. Use when building AI-powered applications that need geospatial capabilities.
Extend Pydantic AI agents with batteries-included capabilities from pydantic-ai-harness — currently Code Mode, which collapses many tool calls into one sandboxed Python execution. Use when the user mentions pydantic-ai-harness, CodeMode, Monty, code mode, or tool sandboxing, when they want an agent to run agent-written Python, or when a Pydantic AI agent would benefit from orchestrating multiple tool calls in a single sandboxed script.
Build AI agents with Pydantic AI (Python) and Claude SDK (Node.js)
Build agentic UIs using AG-UI protocol with Pydantic AI (Python backend) and CopilotKit (React/Next.js frontend). Use when creating AI-powered applications that need bidirectional agent-UI communication, shared state between frontend and backend, human-in-the-loop workflows, tool-based generative UI, or predictive state updates. Triggers on requests involving CopilotKit hooks (useCoAgent, useCopilotAction, useCoAgentStateRender), pydantic_ai with ag_ui adapters, or building chat interfaces with backend AI agents.