Tool Use

What is Tool Use?

Tool use is the capability of AI models to invoke external functions, APIs, databases, and systems to accomplish tasks. It's what transforms a language model from a text-generation system into an agent that can take real actions in the world.

When a model has tool use capabilities:

• It can call functions with appropriate parameters
• It receives results from those function calls
• It incorporates results into its reasoning and responses
• It chains multiple tools to complete complex tasks

Why Tool Use Matters

Before tool use: "I can't access real-time data or take actions—I can only work with text."

After tool use: "Let me check your account balance, schedule that meeting, and send the confirmation email."

Tool use is the bridge between AI understanding language and AI doing work.

How It Works

The Basic Flow

1. User request: "What's the weather in Tokyo?"
2. Model recognizes: This requires external data
3. Model calls tool: get_weather(location="Tokyo")
4. System executes: Calls weather API, returns data
5. Model responds: "It's 72°F and sunny in Tokyo"

Tool Definition Example

{
  "name": "send_email",
  "description": "Send an email to a recipient",
  "parameters": {
    "to": { "type": "string", "description": "Recipient email" },
    "subject": { "type": "string", "description": "Email subject" },
    "body": { "type": "string", "description": "Email content" }
  }
}

The model learns when and how to use this tool from the definition and examples.

Types of Tools

Information Retrieval

• Database queries
• Web search
• Document lookup
• API data fetching

Actions

• Sending emails/messages
• Creating/updating records
• Scheduling events
• Processing payments

Computation

• Running code
• Data analysis
• Mathematical calculations
• File manipulation

Multi-modal

• Image generation
• Voice synthesis
• Document creation

Implementation Approaches

Native Function Calling

Built into model APIs (OpenAI, Anthropic, Google):

• Model outputs structured function calls
• Application executes and returns results
• Most reliable, vendor-supported

Model Context Protocol (MCP)

Anthropic's open standard for tool integration:

• Standardized tool definitions
• Works across different applications
• Growing ecosystem of pre-built tools

Agent Frameworks

LangChain, AutoGPT, CrewAI:

• Orchestrate multiple tools
• Handle complex multi-step workflows
• Add memory and planning

Enterprise Tool Categories

Security Considerations

Tool use introduces real risks:

• Data exposure: Tools may access sensitive information
• Action authority: What should agents be allowed to do?
• Prompt injection: Malicious inputs triggering unintended tool calls
• Rate limits: Agents can make many API calls quickly
• Audit trails: Tracking what actions were taken and why

The Tool Use Revolution

Tool use transforms AI from a productivity enhancer to a work executor. The models that excel at tool use—understanding when to use which tool, handling errors gracefully, chaining tools effectively—will power the next generation of AI agents.

Related Reading

• AI Agents - Systems built on tool use
• Enterprise AI - Where tool use creates business value