Introduction

Building applications with the Claude API is powerful, but keeping up with SDK updates, tool use patterns, and the latest features can be overwhelming. The Claude API Skill solves this by giving Claude itself a deep, up-to-date reference for the Anthropic platform. This open-source Agent Skill equips Claude with detailed documentation for the Messages API and Managed Agents (beta), covering 8 programming languages and 7 languages respectively.

In this guide, you'll learn what the Claude API Skill provides, how it activates automatically, and how to leverage it for faster development, debugging, and optimization of your Claude-powered projects.

What Is the Claude API Skill?

The Claude API Skill is an open-source Agent Skill that provides Claude with:

• Messages API documentation — language-specific SDK installation, quick starts, common patterns, error handling, tool use, streaming, batch processing, prompt caching, and model migration.
• Managed Agents documentation (beta) — onboarding flows, persistent agent creation, session management, streaming events, tool confirmations, and deployment constraints.
• Progressive disclosure — Claude loads only the documentation relevant to your project's language, surface (Messages API or Managed Agents), and specific task (tool use, streaming, batches, etc.), keeping context efficient.

The skill comes bundled with Claude Code and is also available in the Anthropic skills repository for installation in any environment that supports Agent Skills.

Supported Languages and Surfaces

How the Skill Activates

The skill activates in two ways:

Automatic Activation

Claude automatically loads the skill when:

• Your code imports an Anthropic SDK (anthropic for Python, @anthropic-ai/sdk for TypeScript/JavaScript)
• You ask Claude to help build, debug, or optimize something with the Claude API, an Anthropic SDK, or Managed Agents
• You add, modify, or tune a Claude feature in a file (prompt caching, tool use, streaming, etc.)

Manual Activation

You can explicitly trigger the skill using the /claude-api command in environments that support Agent Skills (like Claude Code).

What the Skill Provides in Practice

1. Language-Specific SDK Documentation

When you're working with a specific language, the skill provides Claude with:

# Example: Python SDK installation and quick start
The skill knows the latest SDK version and patterns
import anthropic
client = anthropic.Anthropic()
message = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello, Claude"}]
)
print(message.content)

// Example: TypeScript SDK usage
import Anthropic from '@anthropic-ai/sdk';
const client = new Anthropic();
const message = await client.messages.create({
  model: 'claude-sonnet-4-20250514',
  max_tokens: 1024,
  messages: [{ role: 'user', content: 'Hello, Claude' }]
});
console.log(message.content);

2. Tool Use Guidance

The skill provides language-specific examples for function calling, including the beta tool runner where available:

# Tool use with Python SDK
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    tools=[
        {
            "name": "get_weather",
            "description": "Get the current weather for a location",
            "input_schema": {
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                },
                "required": ["location"]
            }
        }
    ],
    messages=[{"role": "user", "content": "What's the weather in San Francisco?"}]
)

3. Streaming Patterns

Build chat UIs with incremental display:

# Streaming with Python SDK
with client.messages.stream(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Tell me a story"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

4. Batch Processing at 50% Cost

Process multiple requests offline:

# Batch processing example
import anthropic
client = anthropic.Anthropic()
batch = client.messages.batches.create(
    requests=[
        {
            "custom_id": "req-1",
            "params": {
                "model": "claude-sonnet-4-20250514",
                "max_tokens": 1024,
                "messages": [{"role": "user", "content": "Summarize this article"}]
            }
        },
        {
            "custom_id": "req-2",
            "params": {
                "model": "claude-sonnet-4-20250514",
                "max_tokens": 1024,
                "messages": [{"role": "user", "content": "Translate to French"}]
            }
        }
    ]
)

5. Prompt Caching Best Practices

The skill provides guidance on:

• Prefix-stability design
• Breakpoint placement
• Silent-invalidator audit

# Prompt caching with Python SDK
response = client.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1024,
    system=[
        {
            "type": "text",
            "text": "You are a helpful assistant.",
            "cache_control": {"type": "ephemeral"}
        }
    ],
    messages=[{"role": "user", "content": "Hello"}]
)

6. Model Migration Guidance

When migrating to newer Claude models (including breaking changes on Claude Opus 4.7), the skill provides step-by-step migration paths.

7. Managed Agents (Beta) Support

For Managed Agents, the skill offers:

• Onboarding flow: An interview-driven walkthrough via /claude-api managed-agents-onboard
• Language-specific docs: Creating persistent agents, starting sessions, streaming events, and handling tool confirmations
• Client patterns: Lossless stream reconnect, processed_at queued/processed gate, interrupt handling, file-mount gotchas, and credential handling
• Deployment constraints: Managed Agents is first-party only (not available on Amazon Bedrock, Google Vertex AI, or Microsoft Foundry) — the skill routes third-party deployments to Messages API + tool use instead

Progressive Disclosure in Action

The skill's progressive disclosure mechanism is its superpower. Instead of loading all documentation at once (which would waste context), Claude loads only what's relevant:

• Language detection: If your project uses Python, only Python SDK docs are loaded
• Surface detection: If you're using the Messages API, Managed Agents docs are skipped
• Task detection: If you're working on streaming, tool use docs are deferred

This keeps context windows efficient and responses fast.

Installing the Skill

The skill comes bundled with Claude Code. For other environments:

# Clone the skills repository
git clone https://github.com/anthropics/anthropic-skills.git
Navigate to the claude-api skill
cd anthropic-skills/claude-api
Follow installation instructions for your environment

Common Pitfalls the Skill Helps You Avoid

The skill includes detailed guidance on frequent mistakes:

• Incorrect SDK initialization patterns
• Missing error handling for rate limits
• Improper tool call response formatting
• Streaming event handling errors
• Prompt caching breakpoint misplacement

Best Practices for Using the Skill

• Let it activate automatically — Don't manually load the skill unless you need specific subcommands
• Use /claude-api managed-agents-onboard for new Managed Agent projects
• Combine with other skills — The skill works well alongside memory, web fetch, and code execution skills
• Keep your SDKs updated — The skill references the latest SDK versions

Key Takeaways

• The Claude API Skill provides Claude with up-to-date, language-specific documentation for both the Messages API and Managed Agents, covering 8 and 7 programming languages respectively.
• Progressive disclosure keeps context efficient — Claude loads only the documentation relevant to your project's language, surface, and specific task.
• The skill activates automatically when you import an Anthropic SDK or ask Claude to help with API-related tasks, and is bundled with Claude Code.
• It covers essential patterns including tool use, streaming, batch processing, prompt caching, model migration, and Managed Agents onboarding.
• For third-party deployments (Bedrock, Vertex AI, Foundry), the skill automatically routes to Messages API + tool use since Managed Agents is first-party only.