Agent skill

Building AI Chat

by ancoleman in ancoleman/ai-design-components

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support.

MITAuto-check passedFrontend & Design

Install Building AI Chat

skills CLI
$ npx skills add ancoleman/ai-design-components --skill building-ai-chat -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ancoleman/ai-design-components building-ai-chat --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ancoleman/ai-design-components.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/building-ai-chat .claude/skills/building-ai-chat && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
building-ai-chat
GitHub stars
526
Token cost
~3.4k tokens
SKILL.md length
563 words
Files
28 (incl. scripts, references, assets)
Skills in repo
75
Repo updated
First seen
Licence
MIT

At a glance

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support.

  • Works in 5 steps: Perfect timing - Every app adding AI… → No standards exist - Opportunity to… → Meta-advantage - Building WITH Claude =… → …
  • Creating ChatGPT-style interfaces
  • SKILL.md covers Purpose, When to Use, Quick Start and Core Components, plus 10 more sections
  • Calls npm

What it does

Building AI Chat is an agent skill from ancoleman/ai-design-components. Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 30 other files, including scripts, reference files and assets (for example `assets/error-messages.json`, `assets/message-templates.json` and `assets/system-prompts.json`).

It sits in Frontend & Design, covering Context engineering and LLM API integration. It works with OpenAI. The repository describes itself as: Comprehensive UI/UX and Backend component design skills for AI-assisted development with Claude. The licence is MIT.

When your agent uses it

  • Creating ChatGPT-style interfaces
  • Conversational agents

Example prompts

  • “Use the building-ai-chat skill to build AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support”
  • “/building-ai-chat”

Requirements

  • Node.js

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Perfect timing - Every app adding AI (2024-2025 boom)
  2. No standards exist - Opportunity to define patterns
  3. Meta-advantage - Building WITH Claude = intimate UX knowledge
  4. Unique challenges - Streaming, context, hallucinations all new
  5. Reference implementation - Can become the standard others follow

What it can do on your machine

Read from SKILL.md and the folder at commit 76551b7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • npm

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Building AI Chat loads about 3.4k tokens when it runs, and up to ~73k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 563 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~116
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~73k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from ancoleman/ai-design-components at commit 76551b7, republished under its MIT licence (© ancoleman). 563 words, ~3,391 tokens.

Download SKILL.mdSave it as .claude/skills/building-ai-chat/SKILL.md (or your agent's skills folder). This skill also uses 27 other files; get the full folder from GitHub.
name
building-ai-chat
description
Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

AI Chat Interface Components

Purpose

Define the emerging standards for AI/human conversational interfaces in the 2024-2025 AI integration boom. This skill leverages meta-knowledge from building WITH Claude to establish definitive patterns for streaming UX, context management, and multi-modal interactions. As the industry lacks established patterns, this provides the reference implementation others will follow.

When to Use

Activate this skill when:

  • Building ChatGPT-style conversational interfaces
  • Creating AI assistants, copilots, or chatbots
  • Implementing streaming text responses with markdown
  • Managing conversation context and token limits
  • Handling multi-modal inputs (text, images, files, voice)
  • Dealing with AI-specific errors (hallucinations, refusals, limits)
  • Adding feedback mechanisms (thumbs, regeneration, editing)
  • Implementing conversation branching or threading
  • Visualizing tool/function calling

Quick Start

Minimal AI chat interface in under 50 lines:

tsx
import { useChat } from 'ai/react';

export function MinimalAIChat() {
  const { messages, input, handleInputChange, handleSubmit, isLoading, stop } = useChat();

  return (
    <div className="chat-container">
      <div className="messages">
        {messages.map(m => (
          <div key={m.id} className={`message ${m.role}`}>
            <div className="content">{m.content}</div>
          </div>
        ))}
        {isLoading && <div className="thinking">AI is thinking...</div>}
      </div>

      <form onSubmit={handleSubmit} className="input-form">
        <input
          value={input}
          onChange={handleInputChange}
          placeholder="Ask anything..."
          disabled={isLoading}
        />
        {isLoading ? (
          <button type="button" onClick={stop}>Stop</button>
        ) : (
          <button type="submit">Send</button>
        )}
      </form>
    </div>
  );
}

For complete implementation with streaming markdown, see examples/basic-chat.tsx.

Core Components

Message Display

Build user, AI, and system message bubbles with streaming support:

tsx
// User message
<div className="message user">
  <div className="content">{message.content}</div>
  <time className="timestamp">{formatTime(message.timestamp)}</time>
</div>

// AI message with streaming
<div className="message ai">
  <Streamdown className="content">{message.content}</Streamdown>
  {message.isStreaming && <span className="cursor">▊</span>}
</div>

// System message
<div className="message system">
  <Icon type="info" />
  <span>{message.content}</span>
</div>

For markdown rendering, code blocks, and formatting details, see references/message-components.md.

Input Components

Create rich input experiences with attachments and voice:

tsx
<div className="input-container">
  <button onClick={attachFile} aria-label="Attach file">
    <PaperclipIcon />
  </button>

  <textarea
    value={input}
    onChange={handleChange}
    onKeyDown={handleKeyDown}
    placeholder="Type a message..."
    rows={1}
    style={{ height: textareaHeight }}
  />

  <button onClick={toggleVoice} aria-label="Voice input">
    <MicIcon />
  </button>

  <button type="submit" disabled={!input.trim() || isLoading}>
    <SendIcon />
  </button>
</div>
Response Controls

Essential controls for AI responses:

tsx
<div className="response-controls">
  {isStreaming && (
    <button onClick={stop} className="stop-btn">
      Stop generating
    </button>
  )}

  {!isStreaming && (
    <>
      <button onClick={regenerate} aria-label="Regenerate response">
        <RefreshIcon /> Regenerate
      </button>
      <button onClick={continueGeneration} aria-label="Continue">
        Continue
      </button>
      <button onClick={editMessage} aria-label="Edit message">
        <EditIcon /> Edit
      </button>
    </>
  )}
</div>
Feedback Mechanisms

Collect user feedback to improve AI responses:

tsx
<div className="feedback-controls">
  <button
    onClick={() => sendFeedback('positive')}
    aria-label="Good response"
    className={feedback === 'positive' ? 'selected' : ''}
  >
    <ThumbsUpIcon />
  </button>

  <button
    onClick={() => sendFeedback('negative')}
    aria-label="Bad response"
    className={feedback === 'negative' ? 'selected' : ''}
  >
    <ThumbsDownIcon />
  </button>

  <button onClick={copyToClipboard} aria-label="Copy">
    <CopyIcon />
  </button>

  <button onClick={share} aria-label="Share">
    <ShareIcon />
  </button>
</div>

Streaming & Real-Time UX

Progressive rendering of AI responses requires special handling:

tsx
// Use Streamdown for AI streaming (handles incomplete markdown)
import { Streamdown } from '@vercel/streamdown';

// Auto-scroll management
useEffect(() => {
  if (shouldAutoScroll()) {
    messagesEndRef.current?.scrollIntoView({ behavior: 'smooth' });
  }
}, [messages]);

// Smart auto-scroll heuristic
function shouldAutoScroll() {
  const threshold = 100; // px from bottom
  const isNearBottom =
    container.scrollHeight - container.scrollTop - container.clientHeight < threshold;
  const userNotReading = !hasUserScrolledUp && !isTextSelected;
  return isNearBottom && userNotReading;
}

For complete streaming patterns, auto-scroll behavior, and stop generation, see references/streaming-ux.md.

Context Management

Communicate token limits clearly to users:

tsx
// User-friendly token display
function TokenIndicator({ used, total }) {
  const percentage = (used / total) * 100;
  const remaining = total - used;

  return (
    <div className="token-indicator">
      <div className="progress-bar">
        <div className="progress-fill" style={{ width: `${percentage}%` }} />
      </div>
      <span className="token-text">
        {percentage > 80
          ? `⚠️ About ${Math.floor(remaining / 250)} messages left`
          : `${Math.floor(remaining / 250)} pages of conversation remaining`}
      </span>
    </div>
  );
}

For summarization strategies, conversation branching, and organization, see references/context-management.md.

Multi-Modal Support

Handle images, files, and voice inputs:

tsx
// Image upload with preview
function ImageUpload({ onUpload }) {
  return (
    <div
      className="upload-zone"
      onDrop={handleDrop}
      onDragOver={preventDefault}
    >
      <input
        type="file"
        accept="image/*"
        onChange={handleFileSelect}
        multiple
        hidden
        ref={fileInputRef}
      />
      {previews.map(preview => (
        <img key={preview.id} src={preview.url} alt="Upload preview" />
      ))}
    </div>
  );
}

For complete multi-modal patterns including voice and screen sharing, see references/multi-modal.md.

Error Handling

Handle AI-specific errors gracefully:

tsx
// Refusal handling
if (response.type === 'refusal') {
  return (
    <div className="error refusal">
      <Icon type="info" />
      <p>I cannot help with that request.</p>
      <details>
        <summary>Why?</summary>
        <p>{response.reason}</p>
      </details>
      <p>Try asking: {response.suggestion}</p>
    </div>
  );
}

// Rate limit communication
if (error.code === 'RATE_LIMIT') {
  return (
    <div className="error rate-limit">
      <p>Please wait {error.retryAfter} seconds</p>
      <CountdownTimer seconds={error.retryAfter} onComplete={retry} />
    </div>
  );
}

For comprehensive error patterns, see references/error-handling.md.

Tool Usage Visualization

Show when AI is using tools or functions:

tsx
function ToolUsage({ tool }) {
  return (
    <div className="tool-usage">
      <div className="tool-header">
        <Icon type={tool.type} />
        <span>{tool.name}</span>
        {tool.status === 'running' && <Spinner />}
      </div>
      {tool.status === 'complete' && (
        <details>
          <summary>View details</summary>
          <pre>{JSON.stringify(tool.result, null, 2)}</pre>
        </details>
      )}
    </div>
  );
}

For function calling, code execution, and web search patterns, see references/tool-usage.md.

Implementation Guide

Primary libraries (validated November 2025):

bash
# Core AI chat functionality
npm install ai @ai-sdk/react @ai-sdk/openai

# Streaming markdown rendering
npm install @vercel/streamdown

# Syntax highlighting
npm install react-syntax-highlighter

# Security for LLM outputs
npm install dompurify
Performance Optimization

Critical for smooth streaming:

tsx
// Memoize message rendering
const MemoizedMessage = memo(Message, (prev, next) =>
  prev.content === next.content && prev.isStreaming === next.isStreaming
);

// Debounce streaming updates
const debouncedUpdate = useMemo(
  () => debounce(updateMessage, 50),
  []
);

// Virtual scrolling for long conversations
import { VariableSizeList } from 'react-window';

For detailed performance patterns, see references/streaming-ux.md.

Security Considerations

Always sanitize AI outputs:

tsx
import DOMPurify from 'dompurify';

function SafeAIContent({ content }) {
  const sanitized = DOMPurify.sanitize(content, {
    ALLOWED_TAGS: ['p', 'br', 'strong', 'em', 'code', 'pre', 'blockquote', 'ul', 'ol', 'li'],
    ALLOWED_ATTR: ['class']
  });

  return <Streamdown>{sanitized}</Streamdown>;
}
Accessibility

Ensure AI chat is usable by everyone:

tsx
// ARIA live regions for screen readers
<div role="log" aria-live="polite" aria-relevant="additions">
  {messages.map(msg => (
    <article key={msg.id} role="article" aria-label={`${msg.role} message`}>
      {msg.content}
    </article>
  ))}
</div>

// Loading announcements
<div role="status" aria-live="polite" className="sr-only">
  {isLoading ? 'AI is responding' : ''}
</div>

For complete accessibility patterns, see references/accessibility.md.

Bundled Resources

Scripts (Token-Free Execution)
  • Run scripts/parse_stream.js to parse incomplete markdown during streaming
  • Run scripts/calculate_tokens.py to estimate token usage and context limits
  • Run scripts/format_messages.js to format message history for export
Show full SKILL.md (222 more words)Show less
References (Progressive Disclosure)
  • references/streaming-patterns.md - Complete streaming UX patterns
  • references/context-management.md - Token limits and conversation strategies
  • references/multimodal-input.md - Image, file, and voice handling
  • references/feedback-loops.md - User feedback and RLHF patterns
  • references/error-handling.md - AI-specific error scenarios
  • references/tool-usage.md - Visualizing function calls and tool use
  • references/accessibility-chat.md - Screen reader and keyboard support
  • references/library-guide.md - Detailed library documentation
  • references/performance-optimization.md - Streaming performance patterns
Examples
  • examples/basic-chat.tsx - Minimal ChatGPT-style interface
  • examples/streaming-chat.tsx - Advanced streaming with memoization
  • examples/multimodal-chat.tsx - Images and file uploads
  • examples/code-assistant.tsx - IDE-style code copilot
  • examples/tool-calling-chat.tsx - Function calling visualization
Assets
  • assets/system-prompts.json - Curated prompts for different use cases
  • assets/message-templates.json - Pre-built message components
  • assets/error-messages.json - User-friendly error messages
  • assets/themes.json - Light, dark, and high-contrast themes

Design Token Integration

All visual styling uses the design-tokens system:

css
/* Message bubbles use design tokens */
.message.user {
  background: var(--message-user-bg, var(--color-primary));
  color: var(--message-user-text, var(--color-white));
  padding: var(--message-padding, var(--spacing-md));
  border-radius: var(--message-border-radius, var(--radius-lg));
}

.message.ai {
  background: var(--message-ai-bg, var(--color-gray-100));
  color: var(--message-ai-text, var(--color-text-primary));
}

See skills/design-tokens/ for complete theming system.

Key Innovations

This skill provides industry-first solutions for:

  • Memoized streaming rendering - 10-50x performance improvement
  • Intelligent auto-scroll - User activity-aware scrolling
  • Token metaphors - User-friendly context communication
  • Incomplete markdown handling - Graceful partial rendering
  • RLHF patterns - Effective feedback collection
  • Conversation branching - Non-linear conversation trees
  • Multi-modal integration - Seamless file/image/voice handling
  • Accessibility-first - Built-in screen reader support

Strategic Importance

This is THE most critical skill because:

  1. Perfect timing - Every app adding AI (2024-2025 boom)
  2. No standards exist - Opportunity to define patterns
  3. Meta-advantage - Building WITH Claude = intimate UX knowledge
  4. Unique challenges - Streaming, context, hallucinations all new
  5. Reference implementation - Can become the standard others follow

Master this skill to lead the AI interface revolution.

© ancoleman, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 27 other files (scripts, references, assets) in skills/building-ai-chat of ancoleman/ai-design-components.

  • SKILL.md
  • assets/error-messages.json
  • assets/message-templates.json
  • assets/system-prompts.json
  • assets/themes.json
  • examples/basic-chat.tsx
  • examples/code-assistant.tsx
  • examples/multimodal-chat.tsx
  • examples/streaming-chat.tsx
  • examples/tool-calling-chat.tsx
  • outputs.yaml
  • references/accessibility-chat.md
  • references/accessibility.md
  • references/context-management.md
  • references/error-handling.md
  • references/feedback-loops.md
  • references/library-guide.md
  • references/message-components.md
  • … and 10 more

Open the folder on GitHubat commit 76551b7

Compare with similar skills

Building AI Chat next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Building AI Chat compared with similar skills
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Building AI Chat this skillancoleman/ai-design-components526—~3.4kAutomated safety check: PassMIT
Codex Huge Context Setupsteipete/agent-scripts7.3k—~4kAutomated safety check: WarnMIT
Cursor BYOK Prefix Stabilityleookun/cursor-byok3.2k—~1.3kAutomated safety check: PassMIT
Agents Best PracticesDenisSergeevitch/agents-best-practices2.4k—~7.4kAutomated safety check: PassMIT
Claudish UsageMadAppGang/claudish1k—~9kAutomated safety check: PassNone
Talking Avatar Voice Chat Appbuildfastwithai/gen-ai-experiments785—~1.7kAutomated safety check: PassMIT

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Works with

Questions about Building AI Chat

What does Building AI Chat do?

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Building AI Chat is an agent skill from ancoleman/ai-design-components. Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support.

When should I use Building AI Chat?

Building AI Chat fits situations like: creating ChatGPT-style interfaces; conversational agents.

How do I install Building AI Chat in Claude Code?

Run `npx skills add ancoleman/ai-design-components --skill building-ai-chat -a claude-code`. Or copy the skill folder (skills/building-ai-chat in ancoleman/ai-design-components) into .claude/skills/building-ai-chat in your project. Claude Code loads it when a task matches its description.

How do I install Building AI Chat in Codex?

Run `npx skills add ancoleman/ai-design-components --skill building-ai-chat -a codex`. Or copy the skill folder (skills/building-ai-chat in ancoleman/ai-design-components) into .agents/skills/building-ai-chat in your project. Codex loads it when a task matches its description.

Can I use Building AI Chat in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ancoleman/ai-design-components --skill building-ai-chat -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/building-ai-chat, .gemini/skills/building-ai-chat, .github/skills/building-ai-chat and .opencode/skills/building-ai-chat in your project.

What does Building AI Chat need to run?

Going by SKILL.md and its folder, Building AI Chat needs the command-line tools its instructions call (npm). Our summary lists: Node.js.

Does Building AI Chat access the network?

SKILL.md contains no URLs. Its commands use npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Building AI Chat safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Building AI Chat use?

Building AI Chat is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Building AI Chat use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 69k tokens, read only when the agent opens those files.

What are the alternatives to Building AI Chat?

Skills that share tags, products or a category with Building AI Chat: Codex Huge Context Setup (steipete/agent-scripts, 7.3k stars), Cursor BYOK Prefix Stability (leookun/cursor-byok, 3.2k stars), Agents Best Practices (DenisSergeevitch/agents-best-practices, 2.4k stars) and Claudish Usage (MadAppGang/claudish, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Building AI Chat?

ancoleman (a GitHub user) maintains it in ancoleman/ai-design-components, which has 526 GitHub stars. The repository holds 75 skills in this directory. The repository was last updated on December 11, 2025.

Source: ancoleman/ai-design-components on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.