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Tool design ​

A tool the model never calls is worse than no tool: it costs context on every turn and does nothing. Most tool problems are description problems.

The description is prompt ​

The model decides from it, literally.

ts
description: "File operations.";                                  // vague
description: "Reads a project file. Use before answering about code."; // decidable

Write it as an instruction to a colleague who cannot see your code: what it does, and when to reach for it. .describe() on schema fields is read too:

ts
schema: z.object({
  path: z.string().describe("relative path from the project root, e.g. src/main.ts"),
});

Make the schema narrow ​

Every constraint you express is a class of failure the model cannot produce, caught before your code runs:

ts
schema: z.object({
  path: z.string(),
  lines: z.number().int().min(1).max(500).default(100),
  mode: z.enum(["read", "stat"]),
});

An enum beats a free string. A default removes a decision. Invalid arguments never reach execute — the model is told what was wrong and tries again.

Return a budget, not a firehose ​

Tool output is the fastest way to fill a context window, and it is what ages worst: the model rarely needs a whole file ten turns later.

ts
const MAX_CHARS = 4000;

async execute({ path }: { path: string }) {
  const text = await readFile(path, "utf8");
  return text.length <= MAX_CHARS
    ? text
    : `${text.slice(0, MAX_CHARS)}\n… [truncated, ${text.length} chars total]`;
}

Saying you truncated matters — otherwise the model treats a partial file as the whole file.

Write the error the model reads ​

ts
return { content: `No file at "${path}". Check the path.`, isError: true };

ENOENT: no such file or directory, open 'READMEE.md' describes a syscall. The version above tells the model what to do next. See Errors.

And for what the model cannot fix, FatalToolError — which also keeps a driver's message out of the model's context and off your disk.

One tool, one verb ​

A manage_files tool with an action parameter forces the model to make two decisions at once, and the second one is invisible in the tool list. Prefer:

read_file · write_file · list_files

The exception is when the operations genuinely share arguments and only one is ever correct — a search with a kind filter, say.

Keep it a pure function where you can ​

By default execute receives only the validated arguments, which makes the tool trivial to unit-test:

ts
expect(await new ReadFileTool().execute({ path: "x.txt" })).toBe("hello");

Every @context() and @state() you add trades that away. Add them when you need them — passing a signal, recording into the flow's state, starting a nested run — not by default.

Pass the signal ​

Anything that takes time:

ts
async execute(@input() { url }: { url: string }, @context() ctx: Context) {
  const res = await fetch(url, { signal: ctx.signal });
  return res.text();
}

Without it, cancellation only takes effect between steps.

data for what the model should not read ​

ts
return {
  content: `Found 42 matches.`, // what the model sees
  data: { matches, queryMs: 18 }, // for hooks, the report, telemetry
};

Structured detail belongs here rather than serialised into the observation.

Only hand over what is needed ​

The tools array is the security boundary — the agent can do exactly what is in it and nothing else. An agent that reads untrusted content and holds a tool with side effects is an attack surface. A shell tool is the clearest example — see the warning on it in Tool recipes.

Prefer a narrow tool over a general one: restart_service(name) with an enum of known services beats run_shell(command).

Diagnosing "it did not use my tool" ​

  1. Read the description as the model does. Does it say when?
  2. Check the prompt tells it to act. "Before answering, read the relevant files."
  3. Check toolCallSource on the chat nodes in the report. "rescued" means the model wrote the call as text and the framework recovered it — it works, but you are at the edge of the model's ability.
  4. Count the tools. Twenty tools is a hard choice for a small model.