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

Need	Pattern	RAG Query
Basic tool use	Tool definitions	"claude tool definition"
Agentic loop	Iterative tool calling	"claude agentic loop"
Computer control	Computer use	"claude computer use"
Deep reasoning	Extended thinking	"claude extended thinking"
Conversation	Message history	"claude conversation history"

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

Symptom	Likely Cause	RAG Query
Tool not called	Bad schema	"tool input_schema"
Tool response ignored	Wrong tool_use_id	"tool_result matching"
Loop never ends	Not checking stop_reason	"stop_reason end_turn"
Rate limit	Too many requests	"anthropic rate limits"
Schema validation error	Wrong JSON schema format	"json schema tool"

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"