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delegation

Hand a sub-task to another agent, a specialist model, or a background job.

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Delegating

Four ways to offload work. They differ in who does it, whether you wait, and what comes back. Picking wrong wastes a model call or loses the result.

ToolRunsYou get backUse when
delegatenow, same swarmthe finished resulta self-contained sub-task
spawn_specialistnow, chosen modelthe finished resultthe sub-task needs a different model or role
mixture_of_agentsnow, several in parallelone merged answerquality matters more than cost
submit_jobin the backgrounda job id, to poll laterit takes minutes and blocks nothing

Before any of them, ask whether you can just do it. Delegation costs a full context build. For anything you can finish in two or three tool calls, doing it yourself is faster and more reliable.

delegate

delegate with task, plus optional context and role.

The delegate starts COLD. It does not see this conversation. Anything it needs must be in task and context: absolute paths, the exact goal, what "done" looks like, and what it must not touch. A vague task returns vague work, and you will not be able to tell that it misunderstood.

Write task as a complete brief a stranger could execute. Include the acceptance criterion explicitly.

spawn_specialist

spawn_specialist with role and task, plus optional context, provider and model.

Same cold start, same briefing rules. Use it when the sub-task wants a specific profile: a stronger model for a hard piece of reasoning, a cheaper one for bulk extraction, a local one for something that must not leave the machine.

Leave provider and model unset unless you have a reason. The default is configured and works; naming a model that is not available fails the whole call.

mixture_of_agents

mixture_of_agents with prompt and candidates, plus optional model, provider and api_base.

Several candidates answer the same prompt, and the answers are merged. Use it for questions where a single pass is unreliable: an open judgement, a design trade-off, a summary that must not miss anything.

Do not use it for anything deterministic. Running a command, reading a file or computing a value has one right answer; asking three models to vote on it costs several times more and can produce a merged answer that none of them actually gave.

submit_job

submit_job with script, plus optional label.

Runs in the background. Returns a job id immediately.

  1. submit_job with the script. Give it a label, because a bare id is unreadable in a later turn.
  2. Keep working. That is the point.
  3. check_job_status with job_id when you need the result.

Never assume a job succeeded. Poll with check_job_status and read the output before reporting anything about it. Reporting a background job as done without checking is fabrication.

If it is still running when you are otherwise finished, say so explicitly instead of claiming completion.

cancel_job

cancel_job with job_id. It asks for approval, because stopping work is a decision.

It stops the job from continuing. It does NOT undo what the job already did. A script that had written half its files keeps those files; a script that had already called a remote API has already called it. Cancelling is a way to stop spending, not a way to return to the state before the job started.

So after a cancel, read the state before you report anything: list the directory the script was writing to, or query the service it was calling. If you cannot establish what it managed to do, say exactly that. An unknown outcome is a result, and reporting it as "cancelled, nothing happened" is the fabrication this whole page is about.

Cancel when the job is provably pointless: its input was wrong, the user changed their mind, or a faster path is already finished. A job that is merely slow is not a reason.

Traps

  • The delegate cannot see this conversation. The single most common failure. Every path, every constraint, every already-established fact must be restated in task or context.
  • Do not delegate the whole user request. Then you are a relay, you cannot verify anything, and the result arrives with no one having checked it.
  • Delegating something ambiguous multiplies the ambiguity. Resolve it first, or ask the user, then delegate a clear task.
  • Verify what comes back. A delegate reporting success is a claim, not a fact. If it says it wrote a file, read the file.
  • A job id is not a result. Nothing has happened until check_job_status says so.

Failure modes

The delegate returns work that misses the point. The brief was thin. Do not re-run it identically: rewrite task with the missing constraints spelled out, then retry.

The delegate says it cannot find a file that exists. A relative path was passed. It does not share your working directory. Pass absolute paths.

check_job_status reports failure with no detail. Run the same script directly with shell_exec to see the real error. Background output is often truncated.

mixture_of_agents returns a bland merge. The prompt asked for something factual. Do it in one pass instead.

spawn_specialist fails immediately. The named provider or model is not configured. Drop both fields and retry with the default.

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