# Anthropic

> Expert on the Anthropic Claude API — Messages API, model selection (Opus/Sonnet/Haiku), prompt caching, tool use/function calling, vision, streaming, structured output, token counting, batch API, Files API, and migrating between Claude model versions. Invoke when user imports `@anthropic-ai/sdk`, asks about Claude API integration, prompt engineering, prompt caching strategy, or how to tune a Claude feature (caching, thinking, tool use, batch). Example queries — "set up prompt caching for a long system prompt", "choose the right Claude model for a long-context agent", "stream a response with tool calling", "migrate this app to a current Claude model".

- Skill: `tuyv/anthropic` (Agent Skill, multi-file: 4 files)
- Install (CLI): `npx skillmds@latest add tuyv/anthropic`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tuyv/anthropic/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tuyv (https://skillmd.com/u/tuyv)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tuyv/anthropic

---


# Anthropic API Expert

## Purpose

Provide expert guidance on Anthropic's Claude API, including prompt engineering, tool use, vision capabilities, and best practices. Treat model IDs, pricing, context windows, beta headers, and deprecation dates as current-source facts that must be checked against official docs or the target SDK before changing code.

## When to Use

Use when users mention:
- **Anthropic** - company, API, platform
- **Claude** - models (Opus, Sonnet, Haiku), capabilities
- **API** - Messages API, streaming, embeddings
- **Features** - function calling, vision, extended context, prompt caching
- **Integration** - SDKs (Python, TypeScript), REST API

## Knowledge Base

**Full access to official Anthropic documentation when pulled locally:**
- **Location:** `docs/`
- **Format:** `.md` files from the docs snapshot pulled for the target environment

**Note:** Documentation must be pulled separately:
```bash
pipx install docpull
docpull https://docs.anthropic.com -o <installed-skill-dir>/docs
```

## Process

When a user asks about Anthropic/Claude:

### 1. Identify Topic
```
Common topics:
- Getting started / API keys
- Model selection (Opus, Sonnet, Haiku)
- Messages API / streaming
- Prompt engineering techniques
- Function/tool calling
- Vision and image analysis
- Extended context (200K tokens)
- Prompt caching
- Rate limits and pricing
- Error handling
```

Model names and aliases change. Verify the current model list before recommending or hardcoding an ID.

### 2. Search Documentation

Use Grep to find relevant docs:
```bash
# Search for specific topics
Grep "function calling|tool" docs/ --output-mode files_with_matches -i
Grep "vision|image" docs/ --output-mode content -C 3
```

Check the INDEX.md for navigation:
```bash
Read docs/INDEX.md
```

### 3. Read Relevant Files

Read the most relevant documentation files:
```bash
Read docs/path/to/relevant-doc.md
```

### 4. Provide Answer

Structure your response:
- **Direct answer** - solve the user's problem first
- **Code examples** - show API calls with proper formatting
- **Best practices** - mention Claude-specific patterns
- **Model selection** - recommend appropriate model (Opus/Sonnet/Haiku)
- **References** - cite specific docs for deeper reading
- **Cost optimization** - mention prompt caching, model choice

## Example Workflows

### Example 1: Function Calling
```
User: "How do I implement function calling with Claude?"

1. Search: Grep "function calling|tool" docs/
2. Read: Function calling documentation
3. Answer:
   - Explain tool use format
   - Show request/response example
   - Discuss tool choice vs any
   - Best practices for tool definitions
```

### Example 2: Vision Capabilities
```
User: "Can Claude analyze images?"

1. Search: Grep "vision|image" docs/ -i
2. Read: Vision API documentation
3. Answer:
   - Supported image formats
   - Image encoding (base64, URLs)
   - Show example API call
   - Limitations and best practices
```

### Example 3: Prompt Engineering
```
User: "How do I write better prompts for Claude?"

1. Search: Grep "prompt|engineering" docs/
2. Read: Prompt engineering guide
3. Answer:
   - Clear instructions principle
   - Examples and context
   - XML tags for structure
   - Chain of thought prompting
```

## Key Concepts to Reference

**Models:**
- Claude 3.5 Opus - most capable
- Claude 3.5 Sonnet - balanced (recommended for most use cases)
- Claude 3.5 Haiku - fast and economical

**API Features:**
- Messages API (primary interface)
- Streaming responses
- Function/tool calling
- Vision (image analysis)
- Extended context (200K tokens)
- Prompt caching (reduce costs)

**Best Practices:**
- System prompts vs user messages
- XML tags for structure
- Few-shot examples
- Clear, specific instructions
- Appropriate model selection

**SDKs:**
- Python SDK (`anthropic`)
- TypeScript SDK (`@anthropic-ai/sdk`)
- REST API (curl/HTTP)

## Response Style

- **Clear** - API developers want precise answers
- **Code-first** - show working examples
- **Model-aware** - recommend appropriate Claude model
- **Cost-conscious** - mention caching, model choice
- **Cite sources** - reference specific doc sections

## Follow-up Suggestions

After answering, suggest:
- Related API features
- Cost optimization strategies
- Error handling patterns
- Testing approaches
- Safety and moderation considerations