agentbull/ankole/workflow-authoring

Author Workflow scripts

Use the workflow tool for a bounded program that needs parallel subagent tasks, deterministic stages, or both. Use a Background Agent Job for one long task that needs a persistent Codex thread, workspace work, or later human messages. Do not use a Workflow when the main Agent must judge each step before the next step starts.

The workflow tool returns a run_id immediately. Do not poll it. The run wakes the owner Session when it completes or fails. Use show_workflow after that event, or when the human explicitly asks for current status.

Write the program body

The script is the body of an async function. It receives:

• args, the JSON object supplied to the workflow tool
• agent(prompt, opts), which starts one independent subagent task

The script must return its final value. A returned string becomes result text. Another JSON value becomes JSON text.

agent() accepts these options:

• label: a short stable name for status and failure reports
• model_profile: a custom profile when one task needs it
• schema: the non-null result schema for that task

Use labels that describe roles or partitions, such as collect:security, verify:pricing, or round:2:pair:3. Do not put the complete prompt in the label.

A successful call returns its submitted value. A call that exhausts its retry budget returns null. A valid success result cannot be null, so check for null before a later stage uses the value.

Use an explicit top-level schema type: object, array, string, number, integer, or boolean. Prefer a small object with only the fields that the next stage needs. The control plane rejects unsupported schema forms such as $ref and nullable results.

For every object schema, including a nested object, write properties, required, and additionalProperties: false. Put every property name in required exactly once, and do not put another name there. Do not use minProperties or maxProperties. Array item bounds, string bounds and patterns, numeric ranges, integer multipleOf, and enums remain available.

Keep cost visible

Set concurrency and max_agent_calls from the work you can count. Each call attempt is one full model turn, and one call can use as many as three attempts. Ask a task for a decision, compact facts, or a summary instead of source dumps.

Batch wide fanout. Give one task one group of items with an array schema, not one task per item: twenty tasks that each research ten stocks cost one tenth of two hundred single-stock tasks and lose nothing.

Every loop must have a visible finite bound. Do not derive an unbounded loop from subagent output. A run supports at most 1,024 calls, but the deployment default is 32. One result value is at most 24 KiB, and the complete durable memo is at most 6 MiB.

A Workflow task cannot start another Workflow. A Workflow has depth one.

Delegate heavy work from a task

A task can create Background Agent Jobs, then call sleep to hibernate until a job lifecycle event, an owner message, or its deadline wakes it in the same conversation. This makes an agent() call the right unit for deep work: the task does its own triage, writes the job brief from what it found, waits without holding a worker slot, then shapes the job outcome into its result schema.

Write the prompt of a delegating task so it states the deliverable of the job it must create and the schema-shaped summary it must submit afterwards. A delegated job cannot ask a human; a task that needs an owner decision sleeps with attention and a note that states the exact question, and the owner answers with send_message_to_workflow_task.

From the script's view nothing changes: the agent() promise just resolves after hours instead of minutes. Keep delegating stages behind cheap triage stages so only work that deserves a job gets one.

Map and reduce

Start independent calls together. Filter failed values before reduction.

const rows = await Promise.all(
  args.items.map((item, index) =>
    agent(`Analyze this item and return one finding: ${JSON.stringify(item)}`, {
      label: `analyze:${index}`,
      schema: {
        type: "object",
        properties: {
          finding: { type: "string" },
          confidence: { type: "number", minimum: 0, maximum: 1 }
        },
        required: ["finding", "confidence"],
        additionalProperties: false
      }
    })
  )
);
const findings = rows.filter((row) => row !== null);
return { findings };

Run stages

Wait for one batch, then use its compact output in the next batch. Keep the second-stage prompt bounded.

const collected = await Promise.all(
  args.sources.map((source, index) =>
    agent(`Extract up to three claims from ${source}.`, {
      label: `collect:${index}`,
      schema: { type: "array", items: { type: "string" }, maxItems: 3 }
    })
  )
);
const claims = collected.filter((value) => value !== null).flat();
if (claims.length === 0) return { claims: [], verdicts: [] };
const verdicts = await Promise.all(
  claims.map((claim, index) =>
    agent(`Verify this claim and return a short verdict: ${claim}`, {
      label: `verify:${index}`,
      schema: { type: "string", maxLength: 1000 }
    })
  )
);
return { claims, verdicts };

Use a verification panel

Give the same candidate to independent reviewers. Let the script preserve disagreement for the main Agent.

const reviews = await Promise.all(
  ["evidence", "logic", "risk"].map((role) =>
    agent(`Review the candidate for ${role}: ${args.candidate}`, {
      label: `panel:${role}`,
      schema: {
        type: "object",
        properties: {
          pass: { type: "boolean" },
          reason: { type: "string", maxLength: 1200 }
        },
        required: ["pass", "reason"],
        additionalProperties: false
      }
    })
  )
);
return { reviews };

Run a tournament

Reduce a finite candidate set in pairs. A failed comparison keeps the first candidate, so one failed task does not erase the bracket.

let round = args.candidates.slice(0, 32);
for (let roundIndex = 0; round.length > 1 && roundIndex < 5; roundIndex += 1) {
  const next = [];
  for (let index = 0; index < round.length; index += 2) {
    if (index + 1 >= round.length) {
      next.push(round[index]);
      continue;
    }
    const winner = await agent(
      `Choose the stronger candidate and return it exactly: ${JSON.stringify([round[index], round[index + 1]])}`,
      { label: `round:${roundIndex}:pair:${index / 2}`, schema: { type: "string" } }
    );
    next.push(winner === null ? round[index] : winner);
  }
  round = next;
}
return { winner: round[0] ?? null };

The final null in this example is a Workflow result field, not an agent() success value. Do not use a nullable task schema.

Loop until dry

Use a small fixed round limit. Stop early when one round finds no new work.

let frontier = args.seeds.slice(0, 20);
const seen = new Set(frontier);
for (let round = 0; round < 4 && frontier.length > 0; round += 1) {
  const expansions = await Promise.all(
    frontier.map((item, index) =>
      agent(`Find up to three new related items for: ${item}`, {
        label: `expand:${round}:${index}`,
        schema: { type: "array", items: { type: "string" }, maxItems: 3 }
      })
    )
  );
  frontier = expansions
    .filter((value) => value !== null)
    .flat()
    .filter((item) => !seen.has(item))
    .slice(0, 20);
  frontier.forEach((item) => seen.add(item));
}
return { items: [...seen] };

Preserve replay identity

Workflow uses replay with a durable memo. It matches each agent() call by its position and complete arguments. Calls after the longest completed prefix are the live suffix.

Do not change a running script, reorder calls, or build call arguments from an external clock, network response, or file. The runtime gives Date.now() and Math.random() deterministic values, but the clearest script derives calls only from fixed args and earlier task results.

When a run fails, use its failure summaries to distinguish a task failure from script divergence or a size limit. Start a new run with a corrected script; v1 cannot edit and resume the old script.