Menu
Worker-side callback and completion rules for assigned and handed-off tasks in CAO
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
| name | cao-worker-protocols |
| description | Worker-side callback and completion rules for assigned and handed-off tasks in CAO |
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.
Workers receive tasks through one of two orchestration modes:
handoff: blocking work where the orchestrator captures your final output automaticallyassign: non-blocking work where you must actively return results to the requesting terminalDepending 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.
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.
When the task came through assign, send your results back after you finish the work:
send_message(message=...) โ omitting receiver_id routes the result to the terminal that assigned the task (the recorded caller). This is the reliable default.[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.
Return results that are easy for the supervisor to merge into a larger workflow:
If the task asks for progress updates, use send_message for those updates too. Otherwise prefer one final callback with the completed deliverable.
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.
receiver_id).send_message is available and the task requires a callback, call it directly rather than ending with prose alone.Author live dashboard UI from an agent via the `emit_ui` MCP tool. Emit one of six allow-listed components (approval_card, choice_prompt, diff_summary, progress, metric, agent_card) with JSON props and it renders in any AG-UI client watching the fleet. Use when you want the operator to see a decision, a diff, or a status readout instead of scrolling terminal text. Arbitrary HTML/markup is refused.
Author and run CAO Python workflow scripts โ multi-step, parameterized, fan-out orchestrations executed by `cao workflow run`. Use when the user wants a repeatable multi-step job (e.g. data analysis over many files, a review pipeline, a parameterized batch). Authoring ends at a validated script file; running it is a separate, user-approved step.
Create a new CAO (CLI Agent Orchestrator) plugin. Use this skill whenever the user wants to add a plugin that reacts to CAO lifecycle or messaging events, scaffold a plugin package, understand plugin requirements, or integrate an external system (Discord, Slack, dashboards, logging, metrics) with CAO. Also use when the user asks what plugin events are available, how plugin discovery works, or how to install a plugin into a CAO environment.
Create a new CLI agent provider for CAO (CLI Agent Orchestrator). Use this skill whenever the user wants to add support for a new CLI-based AI agent (e.g., a new coding assistant CLI), integrate a new provider, or scaffold a provider implementation. Also use when the user asks about the provider architecture, what files to modify, or how providers work in CAO.
Interact with CAO (CLI Agent Orchestrator) โ launch multi-agent sessions, check status, send follow-up instructions, unblock stuck terminals, or shut down sessions. Use when working with CAO sessions in any capacity.
Enable, operate, and extend CAO's MCP Apps surface โ the sandboxed host-rendered fleet UI (SEP-1865) with the ui://cao/* views, the topology widget, the submit_command mutation choke point, SEP-2133 capability advertisement, and the default-off OAuth scope layer. Use whenever the user wants to turn on the MCP Apps UI, observe/steer a CAO fleet from inside an MCP App host (Claude / Claude Desktop, ChatGPT, VS Code GitHub Copilot, Microsoft 365 Copilot, Goose, Postman, MCPJam, Archestra.AI), debug why the views don't render, build the frontend bundles, or extend the surface (new view, tool, or command kind).