# Cookbook: adding a tool

How to give the model a new capability. Reference implementations: `examples/echo-agent/src/echo-tool.ts` (minimal) and `packages/bash/tool-bash` (production-grade, three-package seam).

## The minimal shape

```ts
import { readFile } from 'node:fs/promises'
import type { Context } from 'cordis'
import { defineTool } from '@deepseek-ai/dsh-tools'

export const name = 'my-tool'
export const inject = ['tools']

export function apply(ctx: Context) {
  ctx.tools.register(defineTool({
    name: 'read_file',
    description: 'Read a file from disk.',          // what the model sees
    parameters: {
      path: { type: 'string', required: true, description: 'Absolute path' },
      limit: { type: 'number' },                     // optional by default
    },
    async execute(args, exec) {
      // args is TYPED from the schema: { path: string; limit?: number }
      // exec carries immutable identity + token; signal is the operational field
      return [{ type: 'text', text: await readFile(args.path, 'utf8') }]
    },
  }))
}
```

Registration is effect-based: disposing the plugin fiber unregisters the tool (write the HMR test). Schemas flow into the system-prompt assembly automatically.

## Rules of the execute() contract

- **Args are validated for you.** `defineTool` validates the model-generated `arguments` against the `SchemaSpec` before `execute` runs (type, required keys, enum membership, nested objects/arrays — [runtime arg validation](../rfc/implemented/architecture/2026-06-11-runtime-arg-validation.md)), so inside `execute` the args already match `InferArgs`. You still hand-check value constraints the DSL can't express (non-empty strings, positive numbers, cross-field rules); throw a descriptive Error for those. Raw JSON-Schema tools registered directly (MCP) are NOT validated by the harness — they validate their own input.
- **Registration snapshots your definition.** Parameters must be losslessly JSON-serializable; the registry validates and clones them, copies the scalar fields, binds each callback once to your definition as its method receiver, and freezes the stored record. Reassigning `definition.execute` after registration does not hot-swap the tool—dispose and register a new definition through the owning effect instead. Deliberate mutable state inside the callback's closure or receiver remains ordinary plugin state.
- **Execution identity is protected.** The registry requires `arguments` to survive lossless-JSON validation before and after cloning, freezes the detached value before policy starts, and assigns an opaque `exec.token`; `callId`, `name`, `arguments`, `agent`, `token`, and an optional enclosing-transport `parent` token stay immutable through dispatch. `parent` is identity-only and exposes no live outer execution. Treat `args` as readonly input. An around-dispatch wrapper may add, replace, or remove only `exec.signal` to impose cancellation or a deadline.
- **Throwing or returning non-JSON data means isError.** The registry catches anything `execute()` throws and validates the complete post-policy result as losslessly JSON-serializable before final observers run. A throw, malformed result, or non-JSON content/context/meta becomes `{isError: true}` so the live outcome cannot succeed and then fail at the durable log. Use errors for infrastructure failures (bad input, spawn errors, aborts), but report domain failures in the result text instead (for example, tool-bash returns `[exit code: 9]` with `isError: false` because the model decides what a failing command means).
- **Honor `exec.signal`.** Cancel in-flight work when it fires.
- **Attach durable card data with `meta` (optional).** `execute` may return `{ content, meta }` instead of a bare `ContentBlock[]` — `meta` is a JSON-serializable payload the core treats as opaque, persisted on the `tool/result` event and handed back to your `presentResult` (so a card that needs more than `args`, like `write`/`edit`'s applied-hunk diff, survives a session replay). Keep UI-only data here, never in the model-facing `content`.
- **Use `exec.agent` for async notifications.** `agent.inject(content, {source: {kind: 'plugin', plugin: '<name>'}})` appends durable context the NEXT model request sees — it is not a wake-up (an idle agent stays idle). Guard against disposed agents (try/catch).

## Long-running work

Follow tool-bash's background pattern: a `run_in_background` flag returns a task id immediately; companion tools poll incrementally and kill; completion notices arrive via `agent.inject()`. Bound buffers and spill full output to disk so nothing is silently lost.

> TODO: each tool reimplements this background pattern by hand today. At some point we need a generic long-running-tool layer that handles task ids, incremental polling, kill, and completion notices uniformly.

## Execution policy and observation

Prefer not to build deployment policy into the tool. Use `tools/pre-execute` for extensible allow/deny/ask policy (the [permission-gate example](./extension-cookbook.md#a-hook-plugin-permission-gate)), `ctx.tools.guard()` for a final monotonic deny that later listeners cannot undo, `tools/execute` to wrap core dispatch with a deadline/retry/metrics scope, `tools/post-execute` to transform or attach model-facing context, and `tools/result` to observe the immutable normalized outcome without changing it. A sandboxing implementation can also sit behind the tool's executor capability seam; the exact contracts are in the [`dsh-tools` README](../../packages/core/tools/README.md#extension-points).

## Code Mode reaches your tool for free

Under the registry's non-native `mode` ([Code Mode](../../packages/core/tools/README.md)), each visible registered capability is callable from a `run_code` program as `await tools.<name>(args)` — nothing to add. The registry keeps `run_code` itself as reserved, unfilterable presentation infrastructure while restrictions still control which end capabilities appear in the scoped SDK and bindings. The generated SDK declares parameters from the same JSON Schema `defineTool` emits (constructs outside that subset degrade to `unknown`); each program call receives its own immutable execution whose `parent` is the enclosing `run_code` token, then re-enters the complete pre/guard/around/post/result pipeline. A failed call rejects the program-side promise with your error text. Design `description` and parameter `description`s as JSDoc a model reads while writing code, and remember that non-text result blocks reach programs as placeholders (text is the bridge's lingua franca).

## How your tool renders in an editor (ACP presentation)

Your tool's `execute` returns model-facing content; its **editor card** is a separate, optional concern you declare with two pure display methods on the `defineTool` options. Design this alongside `execute`, not after — an editor (Zed, over the ACP bridge) shows the card, and a tool with no presentation falls back to a bland generic card (title = tool name, raw args as input).

Both methods return a **`card`-tagged render intent** — pick the card kind that matches what your tool does:

- `presentCall(args)` → a `ToolCallView` (the PENDING card):
  - `{ card: 'generic', title, kind?, rawInput?, content?, locations? }` — the default. Set `kind` for an icon (`read`/`search`/…); set `locations: [{ path, line? }]` for any file your tool touches so a capable editor follows along / jumps to it.
  - `{ card: 'terminal', title, description?, cwd? }` — your call IS a shell command. `title` is the command, `description` renders above the terminal card. (tool-bash.)
  - `{ card: 'diff', title, diffs, locations? }` — your call creates or modifies a file. `diffs: [{ path, oldText, newText }]` (`oldText: null` for a new file) renders as an inline diff card. (tool-fs `write`/`edit`.)
- `presentResult(args, { content, isError, meta? })` → a `ToolResultView` (the COMPLETED card): `{ card: 'generic', title?, content? }`, `{ card: 'terminal', title?, output?, exitCode?, signal? }` (the run's captured output + exit — the bridge shows an exit pill and derives a fenced ` ```console ` fallback for editors without the terminal capability), or `{ card: 'diff', title?, diffs }` (a completed file mutation — the applied hunks computed from the before/after content when there is a before-image, else a whole-file diff for a create; `write`/`edit` attach the hunks via the `meta` channel and read them back here). A mutation tool returns the `diff` result even when it duplicates the call-time card, because an ACP `tool_call_update.content` REPLACES the call's content — a non-diff result would clobber the pending diff. `result.meta` is your tool's own optional presentation payload, attached from `execute` (see below) and persisted so a replay reproduces the card.

Hard rules (they bite if broken):

- **Purity.** These run on live streaming AND on session-log REPLAY, so they must be pure functions of `args` (+ the result) — NO I/O, NO reading session state, NO clock/random. A diff is derived from the args (`write` uses `oldText: null` because a call-time presenter has no prior file content); the BRIDGE, not the tool, fills the session cwd and relativizes a display-path title. If you find yourself wanting the file's old content or the working directory inside `presentCall`, stop — that belongs on the bridge or a future result-event shape, not the presenter.
- **UI-only formatting stays out of the model result.** A fenced ` ```console ` block, a diff, a relativized path — none of these may appear in what `execute` returns to the model; they live only in the presentation. (A `terminal` result view carries RAW `output`; the bridge adds the fences.)
- **`defineTool` soft-validates the display path.** A malformed/older logged arg shape makes the wrapper return `undefined` (a generic fallback) rather than throw — display must never crash a replay.

The neutral vocabulary lives in `dsh-tools` (never import an ACP type into a tool); the ACP bridge maps each `card` to the wire. The design and the why are in [the render-intent-union RFC](../rfc/implemented/architecture/2026-07-02-tool-render-intent-union.md); `dsh-tool-fs` (generic/diff) and `dsh-tool-bash` (terminal) are the reference implementations.

## Tests every tool needs

Arg-validation rejections, result shaping for every outcome, the HMR disposal test, and — for tools with side effects — an integration spec that drives the tool through the agent loop with a scripted `MockAdapter` (`packages/core/agent-loop/tests/mock-adapter.ts`), asserting the `tool/call` / `tool/result` session events. **If your tool has an editor card, also add:** a unit test on `presentCall`/`presentResult` asserting the exact view shape, AND — because a unit test proves the shape but not that an editor renders it — a **snapshot scenario** under `examples/acp-agent/tests/snapshots/` that drives the real tool through the ACP bridge and pins the rendered `tool_call` transcript (the card kind is only verified end-to-end there; see the [ACP snapshot-tests RFC](../rfc/implemented/testing/2026-06-19-acp-snapshot-tests.md)). A tool whose card is a `terminal` needs a scenario whose `input.json` sets `terminalOutput: true` to exercise the capable-client `_meta` path.
