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name: Anthropic Agents description: Workflow patterns and gotchas for Anthropic/Claude agents. Directs to RAG for implementation.

Anthropic Agents Workflow

When to Choose Anthropic/Claude

• Building with Claude models
• Need computer use capabilities
• Want extended thinking (deep reasoning)
• Require strong safety/alignment features

Decision Framework

Pattern Selection

Query RAG: mcp__agentic-rag__query_sdk("pattern example", sdk="anthropic", mode="build")

Critical Gotchas

These are Claude-specific traps:

1. Tool schemas are strict - JSON schema format, not Python type hints
2. tool_use vs tool_result - Tool calls are tool_use, responses are tool_result
3. Tool IDs must match - Response must include the exact tool_use_id
4. ANTHROPIC_API_KEY - Environment variable name is specific
5. Max tokens required - Must specify max_tokens in API calls
6. Stop reason matters - Check stop_reason to know if done or needs tool response
7. Computer use needs beta header - Requires anthropic-beta header

Workflow: Building a Claude Agent

Step 1: SDK Setup

RAG Query: mcp__agentic-rag__query_sdk("anthropic python sdk install", sdk="anthropic", mode="explain")

Step 2: Tool Schema Definition

RAG Query: mcp__agentic-rag__query_sdk("tool input_schema definition", sdk="anthropic", mode="build")

Tools need name, description, input_schema (JSON Schema format).

Step 3: Message Construction

RAG Query: mcp__agentic-rag__query_sdk("messages create tool_choice", sdk="anthropic", mode="build")

Step 4: Tool Response Handling

RAG Query: mcp__agentic-rag__query_sdk("tool_result content block", sdk="anthropic", mode="build")

Match tool_use_id exactly in your response.

Step 5: Agentic Loop

RAG Query: mcp__agentic-rag__query_sdk("agentic loop stop_reason", sdk="anthropic", mode="build")

Loop until stop_reason is not tool_use.

Common Error Patterns

Computer Use

Special capability for GUI automation: RAG Query: mcp__agentic-rag__query_sdk("claude computer use setup", sdk="anthropic", mode="explain")

Requirements:

• Beta header required
• Screenshot handling needed
• Coordinate system understanding

Extended Thinking

For complex reasoning tasks: RAG Query: mcp__agentic-rag__query_sdk("claude extended thinking", sdk="anthropic", mode="explain")

Advanced Features

Query RAG when you need:

• Streaming: "claude streaming response"
• Vision: "claude image input"
• PDF processing: "claude pdf document"
• Caching: "claude prompt caching"
• Batching: "anthropic batch api"