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Found 31 Skills
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
API design and implementation across REST, GraphQL, gRPC, and tRPC patterns. Use when building backend services, public APIs, or service-to-service communication. Covers REST frameworks (FastAPI, Axum, Gin, Hono), GraphQL libraries (Strawberry, async-graphql, gqlgen, Pothos), gRPC (Tonic, Connect-Go), tRPC for TypeScript, pagination strategies (cursor-based, offset-based), rate limiting, caching, versioning, and OpenAPI documentation generation. Includes frontend integration patterns for forms, tables, dashboards, and ai-chat skills.
Batteries-included agent component for React/Next.js from ui.inference.sh. One component with runtime, tools, streaming, approvals, and widgets built in. Capabilities: drop-in agent, human-in-the-loop, client-side tools, form filling. Use for: building AI chat interfaces, agentic UIs, SaaS copilots, assistants. Triggers: agent component, agent ui, chat agent, shadcn agent, react agent, agentic ui, ai assistant ui, copilot ui, inference ui, human in the loop
Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.
Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.
Implement the Syncfusion Blazor AI AssistView component for AI-powered chat interfaces in Blazor applications. Use this skill when implementing conversational AI, chatbots, AI assistants, or prompt-response interfaces. Covers AssistViewPrompt setup, PromptRequested events, markdown responses, and prompt suggestions with avatar customization.
Guide for assistant-ui library - AI chat UI components. Use when asking about architecture, debugging, or understanding the codebase.
使用 @ant-design/x 组件库构建 AI 对话 UI 时使用 —— 涵盖 Bubble、Sender、Conversations、Prompts、ThoughtChain、Actions、Welcome、Attachments、Sources、Suggestion、Think、FileCard、CodeHighlighter、Mermaid、Folder、XProvider 和 Notification。
Generate chat completions using Sarvam AI's Sarvam-M model. Use when the user needs AI chat, text generation, question answering, or reasoning in Indian languages. Sarvam-M is a 24B parameter model with hybrid thinking, superior Indic language understanding, and OpenAI-compatible API. Free to use.
Vercel AI SDK 5 patterns. Trigger: When building AI chat features - breaking changes from v4.
Implement Syncfusion WPF SfAIAssistView for AI chat and conversational assistant interfaces. Use this when building AI assistant UIs, message threads with AI responses, or integrating OpenAI/SemanticKernel in WPF. Covers typing indicators, suggestions, input/response toolbars, stop-responding features, and PromptRequest events using Syncfusion.SfChat.Wpf.
Build scalable customer support systems including help centers, chatbots, ticketing systems, and self-service knowledge bases. Use when designing support infrastructure, reducing support load, improving customer satisfaction, or scaling support without linear hiring.