analysis_claude_code/docs/en/s02-tool-use.md

s02: Tool Use

s01 > [ s02 ] s03 > s04 > s05 > s06 | s07 > s08 > s09 > s10 > s11 > s12

"Adding a tool means adding one handler" -- the loop stays the same; new tools register into the dispatch map.

Harness layer: Tool dispatch -- expanding what the model can reach.

Problem

With only bash, the agent shells out for everything. cat truncates unpredictably, sed fails on special characters, and every bash call is an unconstrained security surface. Dedicated tools like read_file and write_file let you enforce path sandboxing at the tool level.

The key insight: adding tools does not require changing the loop.

Solution

+--------+      +-------+      +------------------+
|  User  | ---> |  LLM  | ---> | Tool Dispatch    |
| prompt |      |       |      | {                |
+--------+      +---+---+      |   bash: run_bash |
                    ^           |   read: run_read |
                    |           |   write: run_wr  |
                    +-----------+   edit: run_edit |
                    tool_result | }                |
                                +------------------+

The dispatch map is a dict: {tool_name: handler_function}.
One lookup replaces any if/elif chain.

How It Works

1. Each tool gets a handler function. Path sandboxing prevents workspace escape.

def safe_path(p: str) -> Path:
    path = (WORKDIR / p).resolve()
    if not path.is_relative_to(WORKDIR):
        raise ValueError(f"Path escapes workspace: {p}")
    return path

def run_read(path: str, limit: int = None) -> str:
    text = safe_path(path).read_text()
    lines = text.splitlines()
    if limit and limit < len(lines):
        lines = lines[:limit]
    return "\n".join(lines)[:50000]

2. The dispatch map links tool names to handlers.

TOOL_HANDLERS = {
    "bash":       lambda **kw: run_bash(kw["command"]),
    "read_file":  lambda **kw: run_read(kw["path"], kw.get("limit")),
    "write_file": lambda **kw: run_write(kw["path"], kw["content"]),
    "edit_file":  lambda **kw: run_edit(kw["path"], kw["old_text"],
                                        kw["new_text"]),
}

3. In the loop, look up the handler by name. The loop body itself is unchanged from s01.

for block in response.content:
    if block.type == "tool_use":
        handler = TOOL_HANDLERS.get(block.name)
        output = handler(**block.input) if handler \
            else f"Unknown tool: {block.name}"
        results.append({
            "type": "tool_result",
            "tool_use_id": block.id,
            "content": output,
        })

Add a tool = add a handler + add a schema entry. The loop never changes.

What Changed From s01

Component	Before (s01)	After (s02)
Tools	1 (bash only)	4 (bash, read, write, edit)
Dispatch	Hardcoded bash call	TOOL_HANDLERS dict
Path safety	None	safe_path() sandbox
Agent loop	Unchanged	Unchanged

Try It

cd learn-claude-code
python agents/s02_tool_use.py

1. Read the file requirements.txt
2. Create a file called greet.py with a greet(name) function
3. Edit greet.py to add a docstring to the function
4. Read greet.py to verify the edit worked