5.  Agent AI

An agent is a program that calls an LLM in a loop, giving the model access to tools (functions it can invoke), and continuing until the model decides it has finished. This chapter covers the tool-use pattern, the agentic loop, a working file-reading agent, and safety constraints.

Why agents instead of single calls?

1. A single call cannot react to its own output. An agent can read a file, see what’s in it, and decide what to read next.
2. Tool use turns the model into an orchestrator: it plans, delegates to tools, and synthesizes results — all without your intervention.
3. Agents can retry failed steps, ask clarifying questions, and handle unexpected inputs gracefully.

5.1  Defining a Tool

tools = [{
    "name": "read_file",
    "description": "Read a source file and return its contents as a string.",
    "input_schema": {
        "type": "object",
        "properties": {
            "path": {"type": "string", "description": "Relative path to the file"}
        },
        "required": ["path"]
    }
}]

5.2  The Tool Loop

import anthropic, pathlib

client = anthropic.Anthropic()
messages = [{"role": "user", "content": "Summarize the file main.py."}]

while True:
    resp = client.messages.create(
        model="claude-sonnet-4-6", max_tokens=2048,
        tools=tools, messages=messages
    )
    if resp.stop_reason == "end_turn":
        print(resp.content[0].text)
        break
    for block in resp.content:
        if block.type == "tool_use":
            text = pathlib.Path(block.input["path"]).read_text()
            messages += [
                {"role": "assistant", "content": resp.content},
                {"role": "user", "content": [{
                    "type": "tool_result",
                    "tool_use_id": block.id,
                    "content": text
                }]}
            ]

5.3  Safety Constraints

An unconstrained agent can do more than intended. Useful guards:

• Cap iterations: for _ in range(MAX_STEPS) — raise an error if exceeded
• Whitelist allowed paths: reject tool calls outside the sandbox directory
• Separate read tools from write tools and require explicit user confirmation before any write tool runs
• Log every tool call and its result to a file for post-session review

5.4  References

Resource	Description
Tool Use Docs	Anthropic’s guide to defining and using tools with the Claude API.
CodeBites: Agent AI	Track page with agent demos and design notes.