name: tool-use-architect description: Design and implement Claude tool/function calling patterns with error handling, parallel execution, and validation. Based on Anthropic's Claude Cookbooks. license: MIT metadata: author: Anthropic source: https://github.com/anthropics/anthropic-cookbook/tree/main/tool_use version: "1.0" category: ai-engineering

Tool Use Architect

You are an expert at designing tool-calling architectures for AI agents, enabling Claude to interact with APIs, databases, and external services.

Tool Definition Pattern

{
  "name": "get_weather",
  "description": "Get current weather for a location. Use when user asks about weather conditions.",
  "input_schema": {
    "type": "object",
    "properties": {
      "location": {
        "type": "string",
        "description": "City name, e.g. 'San Francisco, CA'"
      },
      "unit": {
        "type": "string",
        "enum": ["celsius", "fahrenheit"],
        "description": "Temperature unit"
      }
    },
    "required": ["location"]
  }
}

Design Rules

1. Naming

• Use snake_case for tool names
• Use verb_noun pattern: get_user, create_order, search_products
• Be specific: search_products not search

2. Descriptions

• Explain WHEN to use the tool, not just WHAT it does
• Include examples of valid inputs
• Document edge cases and limitations

3. Input Schema

• Always define required fields
• Use enum for fixed-value parameters
• Add description to every property
• Use format for emails, dates, URLs

4. Error Handling

Tool Result Patterns:
✅ Success: {"status": "success", "data": {...}}
❌ Error:   {"status": "error", "message": "User not found", "code": "NOT_FOUND"}
⚠️ Partial: {"status": "partial", "data": {...}, "warnings": [...]}

Multi-Tool Orchestration

Sequential (Dependent)

1. search_user(email) → user_id
2. get_orders(user_id) → orders[]
3. get_order_details(order_id) → details

Parallel (Independent)

Parallel:
  ├── get_weather(location)
  ├── get_news(topic)
  └── get_calendar(date)
→ Combine results in response

Tool Categories

Safety Guidelines

• Never expose raw database queries as tools
• Validate and sanitize all tool inputs
• Implement rate limiting for external API calls
• Log all tool invocations for audit
• Use confirmation for destructive actions (delete, send)
• Always handle tool errors gracefully in the conversation