Loading...
Loading...
Found 46 Skills
One-shot user management for apps, multi-chain wallet authentication, an AI-powered assistant, and AI app introspection. Use when the user wants to let website users sign in with wallets, email/password, or social login and give each user a wallet-enabled account, then embed EmblemAI chat surfaces, connect plugins, or add Reflexive observability. Provides React components, TypeScript SDKs, session-based authentication, and pointers to the React and agent-wallet skills for specialized workflows.
Create new AI chat interface components for the ai-elements library following established composable patterns, shadcn/ui integration, and Vercel AI SDK conventions. Use when creating new components in packages/elements/src or when the user asks to add a new component to ai-elements.
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.
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.
Three-way conversation between Hayek × Mises × Claude. Multi-role discussion from the perspective of Austrian economics. Trigger: /chatroom-austrian, /austrian-school, "Austrian Chat Room" Austrian economics chatroom. Hayek × Mises × Claude debate. Trigger: /chatroom-austrian, /austrian-school, "Austrian chat"
Guide for Vercel AI SDK v6 implementation patterns including generateText, streamText, ToolLoopAgent, structured output with Output helpers, useChat hook, tool calling, embeddings, middleware, and MCP integration. Use when implementing AI chat interfaces, streaming responses, agentic applications, tool/function calling, text embeddings, workflow patterns, or working with convertToModelMessages and toUIMessageStreamResponse. Activates for AI SDK integration, useChat hook usage, message streaming, agent development, or tool calling tasks.
This skill provides project-specific coding conventions, architectural principles, repository structure standards, testing patterns, and contribution guidelines for the better-chatbot project (https://github.com/cgoinglove/better-chatbot). Use this skill when contributing to or working with better-chatbot to understand the design philosophy and ensure code follows established patterns. Includes: API architecture deep-dive, three-tier tool system (MCP/Workflow/Default), component design patterns, database repository patterns, architectural principles (progressive enhancement, defensive programming, streaming-first), practical templates for adding features (tools, routes, repositories). Use when: working in better-chatbot repository, contributing features/fixes, understanding architectural decisions, following server action validators, implementing tools/workflows, setting up Playwright tests, adding API routes, designing database queries, building UI components, handling multi-AI provider integration Keywords: better-chatbot, chatbot contribution, better-chatbot standards, chatbot development, AI chatbot patterns, API architecture, three-tier tool system, repository pattern, progressive enhancement, defensive programming, streaming-first, compound component pattern, Next.js chatbot, Vercel AI SDK chatbot, MCP tools, workflow builder, server action validators, tool abstraction, DAG workflows, shared business logic, safe() wrapper, tool lifecycle
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.
Guide for assistant-ui library - AI chat UI components. Use when asking about architecture, debugging, or understanding the codebase.
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.
Add automatic stream recovery to AI chat with WorkflowChatTransport, start/resume API endpoints, and the useResumableChat hook.
Enables Claude to interact with Gemini AI chat for quick queries, brainstorming, and alternative AI perspectives