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/cao-worker-protocols

Worker-side callback and completion rules for assigned and handed-off tasks in CAO

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cli-agent-orchestrator
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$ npx -y skills add awslabs/cli-agent-orchestrator --skill cao-worker-protocols --agent claude-code

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How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/cao-worker-protocols

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Worker-side callback and completion rules for assigned and handed-off tasks in CAO

SKILL.md

cao-worker-protocols.SKILL.md
name: cao-worker-protocols
description: Worker-side callback and completion rules for assigned and handed-off tasks in CAO

CAO Worker Protocols

Use this skill when acting as a worker agent inside CLI Agent Orchestrator.

This skill explains how workers should interpret assigned versus handed-off work, when to call `send_message`, and how to report results back cleanly.

Understand the Dispatch Mode

Workers receive tasks through one of two orchestration modes:

  • `handoff`: blocking work where the orchestrator captures your final output automatically
  • `assign`: non-blocking work where you must actively return results to the requesting terminal

Depending on provider and CAO behavior, a handoff may be made explicit in the task text. For example, Codex workers currently receive a `[CAO Handoff]` prefix for blocking handoffs. Other providers may rely on the task wording and orchestration context instead.

Rules for Handoff Tasks

When the task is a blocking handoff, complete the work and present the result in your normal response. The orchestrator captures that response automatically.

Do not call `send_message` for ordinary handoff completion unless the task explicitly asks for additional side-channel communication.

Rules for Assigned Tasks

When the task came through `assign`, send your results back after you finish the work:

1. Format the result clearly and concisely. 2. Call `send_message(message=...)` — omitting `receiver_id` routes the result to the terminal that assigned the task (the recorded caller). This is the reliable default. 3. If the task message names a different callback terminal (directly or in an appended suffix such as `[Assigned by terminal ...]`), pass that ID as `receiver_id` instead.

Do not stop after writing a normal response if the assignment explicitly requires a callback. The requesting terminal depends on `send_message` to receive the result.

Your own `CAO_TERMINAL_ID` identifies your terminal, not the callback target. Never pass it as `receiver_id`.

Message Formatting

Return results that are easy for the supervisor to merge into a larger workflow:

  • Identify what task or dataset the result belongs to
  • Include the requested output or deliverable
  • Keep the message specific enough to act on without re-reading the whole task

If the task asks for progress updates, use `send_message` for those updates too. Otherwise prefer one final callback with the completed deliverable.

Filesystem and Reporting Discipline

If the task asks you to create files, write them before reporting completion. When sending results back to a supervisor, include absolute file paths so the supervisor can continue the workflow without ambiguity.

Reliability Guidelines

  • If the task names an explicit callback terminal, note its ID before you start expensive work; otherwise rely on the default routing (omit `receiver_id`).
  • If `send_message` is available and the task requires a callback, call it directly rather than ending with prose alone.
  • Keep callback messages structured so the supervisor can merge them into a larger workflow.
  • For handoff tasks, return the completed output directly and let the orchestrator handle delivery.
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CLI Agent Orchestrator (CAO) coordinates multiple AI coding CLIs so a supervisor can delegate work to specialist agents in parallel or sequence. 📚 Documentation — guides, reference, and two interactive courses.

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Repo: awslabs/cli-agent-orchestrator