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Found 59 Skills
This skill generates a comprehensive set of Frequently Asked Questions (FAQs) from the course description, course content, learning graphs, concept lists, MicroSims, and glossary terms to help students understand common questions and prepare content for chatbot integration. Use this skill after course description, learning graph, glossary, and at least 30% of chapter content exist.
Azure AI Voice Live SDK for .NET. Build real-time voice AI applications with bidirectional WebSocket communication. Use for voice assistants, conversational AI, real-time speech-to-speech, and voice-enabled chatbots. Triggers: "voice live", "real-time voice", "VoiceLiveClient", "VoiceLiveSession", "voice assistant .NET", "bidirectional audio", "speech-to-speech".
Build AI chat interfaces with custom backends, authentication, and context injection. Use when integrating chat UI with AI agents, adding auth to chat, injecting user/page context, or implementing httpOnly cookie proxies. Covers ChatKitServer, useChatKit, and MCP auth patterns. NOT when building simple chatbots without persistence or custom agent integration.
Build LLM applications using Dify's visual workflow platform. Use when creating AI chatbots, implementing RAG pipelines, developing agents with tools, managing knowledge bases, deploying LLM apps, or building workflows with drag-and-drop. Supports hundreds of LLMs, Docker/Kubernetes deployment.
Build multi-platform chat bots with Chat SDK (`chat` npm package). Use when developers want to (1) Build a Slack, Teams, Google Chat, Discord, GitHub, or Linear bot, (2) Use the Chat SDK to handle mentions, messages, reactions, slash commands, cards, modals, or streaming, (3) Set up webhook handlers for chat platforms, (4) Send interactive cards or stream AI responses to chat platforms. Triggers on "chat sdk", "chat bot", "slack bot", "teams bot", "discord bot", "@chat-adapter", building bots that work across multiple chat platforms.
Proactively apply when generating Slack API payloads with blocks, chat.postMessage calls with structured content, or views.open/views.publish calls. Triggers on Block Kit, Slack blocks, section block, actions block, header block, divider block, context block, table block, markdown block, rich text block, image block, input block, video block, context_actions block, plan block, task_card block, Slack modal, Slack App Home, Slack surfaces, Slack interactive elements, Slack button, Slack select menu, Slack overflow, Slack datepicker, Slack checkboxes, Slack radio buttons, Work Objects, Slack link unfurl, chat.postMessage blocks, views.open, views.update, views.push, views.publish, Slack composition objects. Use when building Block Kit payloads, constructing blocks arrays, creating modals or App Home views, adding interactive elements, implementing link unfurling with Work Objects, or designing rich message layouts. Slack Block Kit UI framework for building rich message layouts, modals, and App Home views.
企业微信客服自动化系统。自动同意好友添加、基于知识库的智能问答、未知问题人工介入提醒。适用于企业微信客服场景的 AI 助手机器人。
Use when detecting ambiguous user intent, hedging language, open-ended framing, personal context before requests, or when unsure whether user wants exploration vs direct answer. Applies to all conversations.
Two-way integration channel between Feishu (Lark/Feishu) and OpenClaw. It implements message receiving and sending through Feishu bot, supporting private chat, group chat, @mention detection, card messages, and file transfer. This skill is used when you need to interact with AI assistants via Feishu, receive Feishu messages to trigger AI responses, or send messages from OpenClaw to Feishu. Difference from feishu-automation: this skill focuses on message channel integration, while feishu-automation focuses on automated operations of Feishu platform (such as multidimensional tables, documents, etc.)
This skill should be used when users need to work with the Vercel AI SDK for building AI-powered applications. It provides comprehensive guidance on core APIs (generateText, streamText), UI components (useChat, useCompletion), tool calling, structured data generation, provider management, streaming protocols, and advanced features like middleware and custom providers.
Exhaustive, source-accurate guide for building iMessage applications using @photon-ai/imessage-kit (Basic) and @photon-ai/advanced-imessage-kit (Advanced). Covers every method, type, option, event, and pattern for iMessage automation, AI agents, and chat bots.