Smithery Logo
MCPsSkillsDocsPricing
Login
Smithery Logo

Accelerating the Agent Economy

Resources

DocumentationPrivacy PolicySystem Status

Company

PricingAboutBlog

Connect

© 2026 Smithery. All rights reserved.

    nathanonn

    ai-elements

    nathanonn/ai-elements
    AI & ML
    1

    About

    SKILL.md

    Install

    Install via Skills CLI

    or add to your agent
    • Claude Code
      Claude Code
    • Codex
      Codex
    • OpenClaw
      OpenClaw
    • Cursor
      Cursor
    • Amp
      Amp
    • GitHub Copilot
      GitHub Copilot
    • Gemini CLI
      Gemini CLI
    • Kilo Code
      Kilo Code
    • Junie
      Junie
    • Replit
      Replit
    • Windsurf
      Windsurf
    • Cline
      Cline
    • Continue
      Continue
    • OpenCode
      OpenCode
    • OpenHands
      OpenHands
    • Roo Code
      Roo Code
    • Augment
      Augment
    • Goose
      Goose
    • Trae
      Trae
    • Zencoder
      Zencoder
    • Antigravity
      Antigravity
    ├─
    ├─
    └─

    About

    Intelligent documentation system for AI Elements component library.

    SKILL.md

    AI Elements Documentation

    Overview

    Provide intelligent documentation retrieval for the AI Elements component library when building AI-native applications. AI Elements is a component library built on shadcn/ui that provides pre-built components like conversations, messages, prompts, workflows, and more - all designed to integrate with the AI SDK.

    This skill automatically fetches relevant documentation from the bundled markdown files and provides context-aware routing to ensure users get the right information format for their query.

    Activation

    Automatically Activate When:

    1. AI Elements Component Names Mentioned:

      • Chat & Messaging: Message, Conversation, Response, Loader, Prompt Input, Suggestion, Actions
      • AI-Specific: Tool, Reasoning, Chain of Thought, Plan, Task, Queue, Artifact
      • Workflow: Canvas, Node, Edge, Connection, Toolbar, Panel, Controls
      • UI Enhancements: Code Block, Image, Sources, Inline Citation, Confirmation, etc.
    2. AI Elements Library Terms:

      • "ai-elements", "AI Elements library"
      • "ai-native app", "AI native application"
      • "shadcn AI components"
      • "@ai-elements/..." (component installation syntax)
    3. File Context Detection:

      • Imports from @/components/ai-elements/
      • Component usage matching AI Elements component names
      • AI Elements commands in package.json
    4. AI-Native Development Queries:

      • Building chat interfaces with AI responses
      • Creating workflow visualizations for AI agents
      • Displaying AI reasoning or chain-of-thought
      • Implementing AI artifact containers

    Do NOT Activate For:

    • Generic chat/messaging apps without AI context
    • General React Flow usage without AI workflow context
    • Standard UI components unless specifically AI Elements components
    • Generic "conversation" mentions without AI/component context

    Core Capabilities

    1. Context-Aware Documentation Routing

    Route queries intelligently based on intent to provide the most useful documentation format:

    Route 1: Implementation Queries → Examples + Components

    Triggers:

    • "how to build...", "create a...", "implement a..."
    • "building a chatbot", "creating a workflow visualization"
    • "I want to make...", "I need to develop..."

    Action:

    1. Identify the most relevant example from INDEX.md
    2. Read the example file using Read tool: .claude/skills/ai-elements/docs/examples/[example].md
    3. Identify 2-3 key components mentioned in the example
    4. Read those component files: .claude/skills/ai-elements/docs/components/[component].md
    5. Present with integration pattern explanation

    Example Query: "How do I build a chatbot with reasoning?" Fetch:

    • docs/examples/chatbot.md
    • docs/components/reasoning.md
    • docs/components/conversation.md

    Route 2: API Reference Queries → Component Only

    Triggers:

    • "what is...", "what does... do", "what props..."
    • "how does X component work"
    • "show me the API for..."
    • "what properties does... accept"

    Action:

    1. Look up component in INDEX.md
    2. Read single component file: .claude/skills/ai-elements/docs/components/[component].md
    3. Suggest 2-3 category-related components from INDEX.md

    Example Query: "What props does Message accept?" Fetch:

    • docs/components/message.md Suggest: Conversation, Response, Actions (same category)

    Route 3: General Guidance Queries → Overview Docs

    Triggers:

    • "getting started with AI Elements"
    • "how to install...", "setup..."
    • "troubleshooting...", "common issues..."
    • "best practices for..."

    Action:

    1. Read appropriate general documentation:
      • docs/introduction.md for getting started
      • docs/usage.md for implementation patterns
      • docs/troubleshooting.md for issues
      • docs/README.md for overview

    Example Query: "I'm new to AI Elements, how do I get started?" Fetch:

    • docs/introduction.md
    • docs/usage.md

    Route 4: Category/Use Case Queries → README + Components

    Triggers:

    • "components for building chat interfaces"
    • "workflow visualization components"
    • "what components help with..."
    • "show me all... components"

    Action:

    1. Read docs/README.md (contains categorized component lists)
    2. Optionally read 1-2 key components in that category
    3. List all relevant components with brief descriptions from INDEX.md

    Example Query: "What components help with workflow visualization?" Fetch:

    • docs/README.md
    • Optionally: docs/components/canvas.md

    2. Smart Multi-Page Fetching

    Fetch Multiple Pages (2-4 total) When:

    • Implementation queries ("how to build...")
    • Query mentions multiple components ("chat with reasoning")
    • Component docs reference other required components
    • Related component sets (Canvas + Node + Edge, Message + Conversation + Response)

    Fetch Single Page When:

    • Simple reference queries ("what props...")
    • Troubleshooting lookups
    • General overview requests

    Stop Fetching When:

    • Already fetched 3-4 pages
    • Query is answered sufficiently
    • Additional pages would be tangential

    3. Category-Aware Suggestions

    After fetching documentation, always suggest 2-3 related components using these category groupings:

    Chat & Messaging:

    • Message, Conversation, Response, Loader, Prompt Input, Suggestion, Actions

    AI-Specific Features:

    • Tool, Reasoning, Chain of Thought, Plan, Task, Queue, Artifact

    Workflow & Canvas:

    • Canvas, Node, Edge, Connection, Toolbar, Panel, Controls

    UI Enhancements:

    • Code Block, Image, Sources, Inline Citation, Web Preview, Shimmer, Open in Chat, Confirmation, Context, Branch

    Common Pairings:

    • Message → Conversation, Response, Actions
    • Reasoning → Chain of Thought, Plan, Task
    • Canvas → Node, Edge, Toolbar, Panel
    • Prompt Input → Suggestion, Confirmation
    • Tool → Artifact, Code Block
    • Sources → Inline Citation

    Suggest components from:

    1. Same category (highest priority)
    2. Commonly used together
    3. Next implementation step

    4. Installation Command Generation

    Always include installation commands in responses:

    Single component:

    **Installation:**
    `npx ai-elements add [component-name]`
    

    Multiple components:

    **Installation:**
    `npx ai-elements add message conversation response`
    

    All components:

    **Installation (all components):**
    `npx ai-elements add @ai-elements/all`
    

    For workflow components (Canvas, Node, Edge, etc.):

    **Installation:**
    `npx ai-elements add canvas` (requires React Flow)
    

    Response Formats

    Single-Page Response Format

    I've fetched the [Component Name] documentation from AI Elements.
    
    **Installation:**
    `npx ai-elements add [component-name]`
    
    [Full component documentation content from file]
    
    ---
    
    **Related Components:**
    - **[Component 1]** - [Brief description of relationship]
    - **[Component 2]** - [Brief description of relationship]
    - **[Component 3]** - [Brief description of relationship]
    

    Multi-Page Response Format

    This requires understanding multiple components. I've fetched:
    
    ---
    
    ## [Example/Component 1 Name]
    
    **Installation:**
    `npx ai-elements add [component-name]`
    
    [Full content from file]
    
    ---
    
    ## [Component 2 Name]
    
    **Installation:**
    `npx ai-elements add [component-name]`
    
    [Full content from file]
    
    ---
    
    ## [Component 3 Name] (if needed)
    
    **Installation:**
    `npx ai-elements add [component-name]`
    
    [Full content from file]
    
    ---
    
    **Integration Pattern:**
    [2-3 sentences explaining how these components work together, referencing examples from the documentation]
    
    **Related Resources:**
    - **[Additional Component]** - [Description]
    - **[Tutorial/Example]** - [Description]
    

    Implementation Guidance Scope

    ✅ DO Provide:

    1. Pattern Explanations from Examples

      • "The chatbot example shows using Conversation with auto-scroll"
      • "The workflow example demonstrates connecting Canvas + Node + Edge"
    2. Component Integration Patterns

      • "Typically used together: Message inside Conversation with Response for AI output"
      • "Canvas requires Node and Edge components for complete workflows"
    3. Best Practices from Docs

      • "The docs recommend using Loader during AI response generation"
      • "Prompt Input includes built-in file attachment handling"
    4. Common Pitfall Warnings

      • "Note: Canvas requires React Flow to be installed separately"
      • "Response component uses Streamdown for markdown rendering"
    5. Installation Guidance

      • "Install all chat components: npx ai-elements add message conversation response"
      • "Prerequisites: Next.js with AI SDK and shadcn/ui"

    ❌ DON'T Provide:

    1. Complete Custom Implementations - Reference examples instead of generating new code
    2. Customization Beyond Docs - Only suggest what's documented
    3. Debugging User Code - Can reference troubleshooting docs only
    4. Undocumented Features - Only describe documented capabilities
    5. Framework Integration (unless documented) - Stick to documented Next.js + AI SDK patterns

    Documentation Access

    File Structure

    All documentation is bundled in the skill at:

    .claude/skills/ai-elements/
    ├── SKILL.md (this file)
    ├── INDEX.md (searchable component reference)
    └── docs/
        ├── README.md (overview and categories)
        ├── introduction.md (getting started)
        ├── usage.md (implementation patterns)
        ├── troubleshooting.md (common issues)
        ├── components/ (31 component files)
        │   ├── message.md
        │   ├── conversation.md
        │   ├── reasoning.md
        │   └── ...
        └── examples/ (3 tutorial files)
            ├── chatbot.md
            ├── v0.md
            └── workflow.md
    

    How to Access Documentation

    1. Search INDEX.md for component names, keywords, or categories
    2. Read files using the Read tool with absolute paths:
      • Components: .claude/skills/ai-elements/docs/components/[name].md
      • Examples: .claude/skills/ai-elements/docs/examples/[name].md
      • General: .claude/skills/ai-elements/docs/[name].md
    3. Extract metadata from INDEX.md entries (keywords, related components, categories)
    4. Generate suggestions using category groupings and common pairings

    Query Interpretation Examples

    Example 1: Building a Feature

    Query: "How do I build a chat interface with AI responses?"

    Routing: Implementation query → Examples + Components

    Process:

    1. Search INDEX.md for "chat", "conversation", "chatbot"
    2. Identify relevant example: chatbot.md
    3. Read .claude/skills/ai-elements/docs/examples/chatbot.md
    4. Extract key components mentioned: Conversation, Message, Response
    5. Read those component files
    6. Format multi-page response with integration pattern

    Response includes:

    • Installation commands for all components
    • Full chatbot example
    • Component API references
    • Integration pattern explanation

    Example 2: API Lookup

    Query: "What props does the Reasoning component accept?"

    Routing: API reference query → Component only

    Process:

    1. Look up "reasoning" in INDEX.md
    2. Read .claude/skills/ai-elements/docs/components/reasoning.md
    3. Extract category from INDEX.md: "AI-Specific Features"
    4. Find related components: Chain of Thought, Plan, Task

    Response includes:

    • Installation: npx ai-elements add reasoning
    • Full Reasoning component documentation
    • Props table and usage examples
    • Suggestions: Chain of Thought, Plan, Task

    Example 3: Category Exploration

    Query: "What components help with workflow visualization?"

    Routing: Category query → README + key component

    Process:

    1. Search INDEX.md for "workflow" category
    2. Read .claude/skills/ai-elements/docs/README.md
    3. Extract Workflow & Canvas category section
    4. Optionally read Canvas component as primary example

    Response includes:

    • List of all workflow components
    • Brief descriptions from README
    • Installation command for workflow set
    • Suggestion to check workflow example

    Example 4: Getting Started

    Query: "I'm new to AI Elements, how do I get started?"

    Routing: General guidance → Overview docs

    Process:

    1. Read .claude/skills/ai-elements/docs/introduction.md
    2. Read .claude/skills/ai-elements/docs/usage.md

    Response includes:

    • Installation instructions
    • Prerequisites checklist
    • Basic usage patterns
    • Suggestions to explore chatbot/v0/workflow examples

    Important Notes

    Prerequisites

    Always mention when relevant:

    • Node.js 18 or later
    • Next.js project
    • AI SDK installed
    • shadcn/ui installed
    • React Flow (for workflow components only)

    Component Customization

    Components are installed as source files into the user's codebase (typically @/components/ai-elements/), making them fully customizable. Reference usage.md for customization guidance.

    AI SDK Integration

    All components are designed for use with the AI SDK. Reference integration patterns with useChat, useCompletion, and other AI SDK hooks when showing examples.

    React Flow Dependency

    Canvas, Node, Edge, Connection, Toolbar, Panel, and Controls components require React Flow to be installed separately. Always note this dependency when fetching workflow component documentation.

    Workflow Summary

    For every query:

    1. Identify intent → Implementation, API reference, category, or general guidance
    2. Route appropriately → Determine which files to fetch
    3. Search INDEX.md → Find relevant components, keywords, categories
    4. Read files → Use Read tool to access documentation
    5. Format response → Include installation, content, integration pattern, suggestions
    6. Suggest related → Use category groupings and common pairings

    Keep responses:

    • Focused on documented information
    • Formatted with clear installation commands
    • Enriched with relevant component suggestions
    • Practical with integration patterns from examples
    Repository
    nathanonn/claude-skills-ai-elements
    Files