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workflow: dynamic workflows — script-driven multi-agent orchestration

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A new capability family at packages/workflow/ in the bash seam shape,
modeled on Claude Code's dynamic workflows: the model writes a JavaScript
orchestration script (export const meta = {...} + plain-JS body), a runtime
executes it, and the script — not the conversation — holds the loop, the
branching, and the intermediate results.

- dsh-workflow (ctx.workflows): abstract WorkflowService + run vocabulary
  (WorkflowRun whose result NEVER rejects) + observe-only workflow/* events
  carrying data snapshots (id + meta, never the live run), per-listener
  contained like subagent/*.
- dsh-workflow-vm: in-process node:vm engine. Meta extraction via a
  string/comment-aware scanner (template interpolation rejected; literal
  evaluated alone in an empty timed context; statement blanked line-
  preservingly so stacks keep script line numbers). Hooks: agent(prompt,
  {label, phase, schema, model}) over ctx.subagents, parallel(), pipeline()
  (no cross-stage barrier), phase(), log(), args. Fatal-vs-null discipline:
  hook misuse (unknown/deferred options, bad arguments, unsupported
  schemas, tripped caps, seam start failures, cancellation) throws fatal
  WorkflowErrors the combinators RE-THROW — never dissolved into the
  per-item null reserved for child failures. Realm boundary: inbound values
  materialized by descriptor walks that never invoke accessors (defineProperty
  copies, __proto__-safe); outbound values rebuilt in-realm via the
  context's own JSON.parse. Determinism bans (Date.now/Math.random/argless
  new Date) kept so future resume support cannot break scripts. Caps and
  timeouts are validated Config. Every hook promise carries a no-op
  rejection consumer (app-boot exits on unhandled rejections).
- dsh-tool-workflow: the model-facing workflow tool, synchronous like
  dsh-tool-subagent (start → await → try/finally dispose; abort bridged;
  non-completed → isError). Generic render card titled by a textual
  meta.name sniff. The tool description carries the authoring contract.

Wired into examples/{coding-agent,acp-agent} with explicit-ask-only
guidance. Coverage at every tier: unit (meta scanner, materializer incl.
counting-getter and __proto__ regressions, combinator semantics,
concurrency ceiling, caps, cancellation, no-unhandled-rejection abandon),
integration over the real spawn stack, with-key e2e (real two-phase run +
the tool through the registry pipeline), and a recorded ACP snapshot
scenario (workflow-run, 1 child session). RFC:
docs/rfc/implemented/feature/2026-07-05-dynamic-workflows.md (deferred
work explicitly listed). AGENTS.md budget 1575 → 1590 for the new group's
layout line.
This commit is contained in:
Tianyi Cui
2026-07-05 13:29:35 +08:00
parent dafb81be7b
commit 1d43ea3cd5
52 changed files with 4459 additions and 109 deletions
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18
examples/acp-agent/cordis.yml
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@@ -56,6 +56,12 @@
subagent_fork instead when the subtask needs THIS conversation's
context: the child inherits the log so far.
Use the workflow tool ONLY when the user explicitly asks for a
workflow or for large multi-agent orchestration: you write a
JavaScript script (its 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.
For multi-step work, use the todo_write tool to track a task list:
send the WHOLE list each call (it replaces the previous one), keep at
most one task in_progress (exactly one while work remains), and mark a
@@ -93,6 +99,18 @@
provider: fork
toolName: subagent_fork
# Dynamic workflows: the node:vm engine (ctx.workflows) over the spawn subagent
# backend above, plus the model-facing `workflow` tool. The model writes a
# JavaScript orchestration script (meta + body); the engine runs it in-process
# and fans agent() calls out as spawn children.
- id: workflow-vm
name: '@deepseek-ai/dsh-workflow-vm'
config:
provider: spawn
- id: tool-workflow
name: '@deepseek-ai/dsh-tool-workflow'
# The model-facing todo_write tool: whole-list task tracking written to the
# session log (todo/write), surfaced to the ACP client as a `plan` update.
- id: tool-todo

4
examples/acp-agent/tests/acp.snapshot.ts
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@@ -78,6 +78,10 @@ const SCENARIOS: Scenario[] = [
{ name: 'subagent-multi', hasModelTurn: true, recorded: true, childSessions: 2 },
{ name: 'subagent-fork', hasModelTurn: true, recorded: true, childSessions: 1 },
{ name: 'subagent-mixed', hasModelTurn: true, recorded: true, childSessions: 2 },
// The workflow tool: the model writes a one-child orchestration script; the
// child runs as a spawn subagent inside the vm engine (its session is the
// child fixture), and the tool result carries the script's return value.
{ name: 'workflow-run', hasModelTurn: true, recorded: true, childSessions: 1 },
// Hook matrix — one scenario per hook point × its headline Decision outcome,
// across BOTH bridges (Claude `hooks.json`, Codex `codex-hooks.json`, seeded in
// workspace/). The block scenarios need no model call: a UserPromptSubmit hook

7
examples/acp-agent/tests/snapshots/workflow-run/input.json Normal file
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@@ -0,0 +1,7 @@
{
"steps": [
{ "op": "initialize" },
{ "op": "newSession" },
{ "op": "prompt", "text": "Use the workflow tool exactly once, with args omitted and this EXACT script (copy it verbatim):\nexport const meta = { name: 'snapshot-flow', description: 'one child for the snapshot' }\nphase('Run')\nconst reply = await agent('Reply with exactly the word WF_CHILD_OK and nothing else.')\nreturn { reply }\nAfter the workflow returns, reply with the single word WORKFLOW_DONE and stop. Do not use any other tool." }
]
}

37
examples/acp-agent/tests/snapshots/workflow-run/session.1.jsonl Normal file
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examples/acp-agent/tests/snapshots/workflow-run/session.jsonl Normal file
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75
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{"jsonrpc":"2.0","id":3,"result":{"stopReason":"end_turn"}}