# @deepseek-ai/dsh-tool-workflow

The model-facing **`workflow` tool**: run a JavaScript orchestration script that fans out subagents, and return the script's final value. This package owns schema and lifecycle shaping over [`ctx.workflows`](../workflow/README.md); script parsing, execution, caps, and cancellation live behind the seam, while the consumer retains ownership of the parent-facing schema and result envelope.

## What the model sees

Three parameters: `meta` (required identity data: `name`, `description`, and optional progress annotations), `script` (required plain JavaScript body — no `export const meta` statement; the tool description carries the complete authoring contract), and `args` (optional JSON object exposed to the script as the `args` global; wrap a bare list in a field so the wire schema stays honest). The plugin also contributes a `tool:<toolName>` system-prompt section carrying the usage policy — use the tool only on an explicit user ask for a workflow / large orchestration; prefer plain subagent calls for one or two delegations — per the convention that tool guidance ships with the tool plugin, never in the deployment persona.

## Lifecycle

Collection is SYNCHRONOUS this cut (like [`dsh-tool-subagent`](../../subagent/tool-subagent/README.md)): `execute` starts a run and awaits `run.result` inside a `try/finally` that always disposes the run, so the script and its children reach quiescence on every path. `exec.signal` is bridged to `run.cancel()` (including the already-aborted-before-start case). A non-`completed` stop reason maps to an `isError` result reporting the reason — never partial output as success; a parse/meta failure thrown synchronously by `start()` becomes an `isError` the model can correct from. The completed result renders the meta name, the agent count, and the return value as JSON, truncated at `maxResultChars` with an explicit notice.

## Render intent

Decided up front (per the [render-intent RFC](../../../docs/rfc/implemented/architecture/2026-07-02-tool-render-intent-union.md)): a `generic` card titled `workflow: <meta.name>`, read directly from `args.meta.name` (presentation is a pure function of args and does not ask the engine to parse); the script text rides as `rawInput`. The result keeps the generic card.

## Config

| Key | Default | Meaning |
|---|---|---|
| `toolName` | `workflow` | The model-facing tool name to register. |
| `maxResultChars` | `50000` | Rendered-result ceiling; longer JSON is truncated with a notice. |

## Model Experience

### System prompt

#### What the model sees

Every parent request in this plugin's registration scope receives the workflow guidance below. A scoped tool restriction can hide the schema without removing this independently registered guidance.

##### Workflow guidance

```markdown
Use the <toolName> tool ONLY when the user explicitly asks for a workflow or for large multi-agent orchestration: you write a JavaScript script (the tool description documents the exact format) that fans work out across many subagents with phases and structured results. For one or two delegations, prefer plain subagent calls.
```

#### Token effect

Small fixed guidance cost per request while the plugin is active.

#### KV Cache effect

Prefix-stable while the plugin scope and guidance text are unchanged. Activation or disposal may invalidate reuse from this prompt section.

### Tool schema

#### What the model sees

When visible, the generated default [`workflow` schema](../../../docs/tool-catalog.md#deepseek-aidsh-tool-workflow) carries the complete JavaScript hook and metadata contract; `toolName` can rename the definition, and the model submits script, metadata, and optional args.

#### Token effect

Substantial fixed schema cost on each request where the tool is visible.

#### KV Cache effect

Prefix-stable while `toolName`, definition, and visibility are unchanged. Renaming, plugin lifecycle, or scoped restrictions may invalidate reuse from this schema.

### Tool-call history and result

#### What the model sees

The full model-written script, metadata, and args remain in the assistant tool call. Success is exactly `workflow "<name>" completed (<count> agent<optional-s>).`, newline, `Return value:`, newline, and pretty-printed data-dependent JSON; a cap adds `… [truncated: <omitted> more characters]` on a new line. Failures are exactly `Error: workflow run was cancelled`, optionally suffixed ` (<error>)`, `Error: workflow run failed: <error-or-unknown error>`, or defensively `Error: workflow run ended abnormally (<reason>)`; a call without an owning agent becomes `Error: workflow tool requires a calling agent (exec.agent was undefined)`. Intermediate child messages are omitted.

#### Token effect

Call tokens can be large and remain until compaction. Result rendering is capped by `maxResultChars`; child-model tokens are separate from the parent's retained context.

#### KV Cache effect

Append-only; newly visible content follows the reusable request prefix and does not invalidate existing KV-cache entries.

## Known Limitations and Deferred Work

- **The parent turn blocks until the whole workflow settles** — there is no background start/poll surface, and cancellation discards partial output as an error.
- **`args` must be an object and the result is bounded text** — callers wrap top-level arrays/scalars in a field, and JSON beyond `maxResultChars` is truncated rather than stored behind a retrieval handle.
- **Workflow policy is fixed per tool registration** — provider selection, caps, and tool name are deployment config, not model-call arguments.
