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Found 26 Skills
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.
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
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 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 assistant-ui library - AI chat UI components. Use when asking about architecture, debugging, or understanding the codebase.
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 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.
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.
Chat with Glean Assistant from the command line. Use when asking questions, summarizing documents, or getting AI-powered answers about company knowledge.
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