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Found 84 Skills
Vercel AI SDK (Python) - patterns for building LLM-powered apps with streaming, tools, hooks, and structured output
Migrates Airflow projects from airflow-ai-sdk to apache-airflow-providers-common-ai 0.1.0+. Use this skill when the user wants to replace airflow-ai-sdk with the official Airflow AI provider, migrate LLM decorators (@task.llm, @task.agent, @task.llm_branch, @task.embed), switch from model strings/objects to connection-based LLM configuration, or update imports from airflow_ai_sdk to the new provider. Also trigger when the user mentions common-ai provider, AIP-99, pydanticai connection, or migrating away from airflow-ai-sdk.
Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing.
This skill provides production-ready AI chat UI components built on shadcn/ui for conversational AI interfaces. Use when building ChatGPT-style chat interfaces with streaming responses, tool/function call displays, reasoning visualization, or source citations. Provides 30+ components including Message, Conversation, Response, CodeBlock, Reasoning, Tool, Actions, Sources optimized for Vercel AI SDK v5. Prevents common setup errors with Next.js App Router, Tailwind v4, shadcn/ui integration, AI SDK v5 migration, component composition patterns, voice input browser compatibility, responsive design issues, and streaming optimization. Keywords: ai-elements, vercel-ai-sdk, shadcn, chatbot, conversational-ai, streaming-ui, chat-interface, ai-chat, message-components, conversation-ui, tool-calling, reasoning-display, source-citations, markdown-streaming, function-calling, ai-responses, prompt-input, code-highlighting, web-preview, branch-navigation, thinking-display, perplexity-style, claude-artifacts
Guide for adding new AI provider packages to the AI SDK. Use when creating a new @ai-sdk/<provider> package to integrate an AI service into the SDK.
Use when billing for AI model token usage — setting up @commet/ai-sdk tracked() middleware, configuring balance consumption model plans with AI model pricing, tracking input/output/cache tokens, cost calculation with margins, or building AI products that need usage-based billing.
Build LLM-powered chat apps with the right SDK — Anthropic SDK / Claude API (prompt caching, thinking, tool use, batch, files, citations, memory, model migrations) AND Vercel AI SDK (useChat, streamText, tool calls, UIMessage, ChatStatus, addToolOutput). Use when implementing chat interfaces, tuning Claude features, migrating between Claude model versions, or wiring up streaming with @ai-sdk/react.
Lets end users add, authenticate, and manage MCP servers from the browser in assistant-ui apps with @assistant-ui/react-mcp. Use when building user-managed MCP server UIs: mounting McpManagerResource via useAui({ mcp }), declaring presets with defineConnector, dropping in McpConfigDialog, or composing McpManagerPrimitive (Root, Connectors, CustomServers, AddCustomTrigger), McpServerPrimitive (Root, Name, Icon, Status, ConnectButton, DisconnectButton, OAuthLink, RemoveButton, Error), and McpAddFormPrimitive (NameField, UrlField, AuthSelect, AuthFields, Submit, Cancel). Covers auth modes none/bearer/oauth, the OAuth flow with McpOAuthCallback, connection states, storage via McpLocalStorage/McpMemoryStorage/McpCustomStorage, reading state with useAuiState (s.mcp, s.mcpServer), and imperative addCustomServer/connect/callTool. Distinct from developer-defined backend @ai-sdk/mcp tools in the tools skill. Reach for this when connected-server tools are missing, OAuth never completes, or servers do not persist.
Mem0 CLI -- the command-line interface for mem0 memory operations. TRIGGER when: user mentions "mem0 cli", "mem0 command line", "@mem0/cli", "mem0-cli", "pip install mem0-cli", "npm install -g @mem0/cli", or is running mem0 commands in a terminal/shell (mem0 add, mem0 search, mem0 list, mem0 get, mem0 init, mem0 config, mem0 import). Also triggers when query includes CLI flags like --user-id, --output, --json, --agent, or describes bash/zsh/terminal/shell usage. DO NOT TRIGGER when: user asks about programmatic SDK integration in Python/TS code (use mem0 skill), or Vercel AI SDK provider (use mem0-vercel-ai-sdk skill).
Develop AI-powered applications using Genkit in Go. Use when the user asks to build AI features, agents, flows, or tools in Go using Genkit, or when working with Genkit Go code involving generation, prompts, streaming, tool calling, or model providers.
Develop AI-powered applications using Genkit in Python. Use when the user asks about Genkit, AI agents, flows, or tools in Python, or when encountering Genkit errors, import issues, or API problems.
AI-powered browser automation SDK for web scraping, testing, and workflow automation. Use when automating web browsers, extracting data from websites, testing web applications, or building web automation workflows. Supports both API key and AWS credential authentication.