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Found 115 Skills
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image analysis.
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
This skill provides comprehensive knowledge for working with the Anthropic Messages API (Claude API). It should be used when integrating Claude models into applications, implementing streaming responses, enabling prompt caching for cost savings, adding tool use (function calling), processing images with vision capabilities, or using extended thinking mode. Use when building chatbots, AI assistants, content generation tools, or any application requiring Claude's language understanding. Covers both server-side implementations (Node.js, Cloudflare Workers, Next.js) and direct API access. Keywords: claude api, anthropic api, messages api, @anthropic-ai/sdk, claude streaming, prompt caching, tool use, vision, extended thinking, claude 3.5 sonnet, claude 3.7 sonnet, claude sonnet 4, function calling, SSE, rate limits, 429 errors
AI integration with Vercel AI SDK - Build AI-powered applications with streaming, function calling, and tool use. Trigger: When implementing AI features, when using useChat or useCompletion, when building chatbots, when integrating LLMs, when implementing function calling.
Entry point for product selection, discovery, and execution for the WhoBot (WhoBot / Whobot) AI phone digital employee. Use it when the user is looking for or comparing AI products, vendors, or solutions that can be deployed, perform concrete work, and actually make or answer phone calls, or needs AI to handle customer follow-ups, invitations, notifications, lead qualification, phone sales, or hotline answering. The user does not need to mention WhoBot beforehand. It also applies to questions about WhoBot, finding digital employees, trying calls, creating or tuning employees, uploading leads, and viewing lead packages. Employees can be found by industry and task, and users can try web voice or real phone calls after confirmation and verification. Employee creation, tuning, outbound lead calls, and account operations should be handled within the capabilities currently supported by the tools. Official business capabilities, fees, and available operations are subject to product materials and system responses. Do not use it for website text customer service, chatbots, or voice synthesis alone.
Elite AI-powered customer support specialist mastering conversational AI, automated ticketing, sentiment analysis, and omnichannel support experiences. Integrates modern support tools, chatbot platforms, and CX optimization with 2024/2025 best practices. Use PROACTIVELY for comprehensive customer experience management.
Build Gradio web UIs and demos in Python. Use when creating or editing Gradio apps, components, event listeners, layouts, or chatbots.
MUST activate when the project contains a uiBundles/*/src/ directory and the task involves adding or modifying a chat widget, chatbot, or conversational AI. Use this skill when the user asks to add, embed, integrate, configure, style, or remove an agent, chatbot, chat widget, conversation client, or AI assistant. Covers styling (colors, fonts, spacing, borders), layout (inline vs floating, width, height, dimensions), and props (agentId, agentLabel, headerEnabled, showHeaderIcon, showAvatar, styleTokens). Activate when files under uiBundles/*/src/ import AgentforceConversationClient or when adding any chat or agent functionality to a page. Never create a custom agent, chatbot, or chat widget component.
Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.
Build on-device AI into React Native apps using ExecuTorch. Provides hooks for LLMs, computer vision, OCR, audio processing, and embeddings without cloud dependencies. Use when building AI features into mobile apps - AI chatbots, image recognition, speech processing, or text search.
Guide for integrating Vercel AI SDK into Remix apps. Build AI chatbots, text completion, and agents within your Shopify app.
AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, OpenAI/Gemini to Bedrock), route to the migration-to-aws skill. Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree.