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/orchestrate

@03192a5
by cursorcursor/plugins9.1k stars
857

Use only when the user explicitly types `/orchestrate <goal>` to decompose a large task, spawn a tree of parallel cloud-agent workers/subplanners/verifiers via the Cursor SDK, and collect structured handoffs; do not invoke autonomously.

Use this Skill: https://skilld.dev/gh/cursor/plugins/orchestrate

This session only. Nothing lands on disk.

promptsloop-hygiene.md

≈457 tokens on demand. Your agent reads this file only when SKILL.md points to it.

Loop hygiene:

  • Run bun cli.ts run{{rootFlag}} <workspace> in the foreground. The Shell default backgrounds the loop and breaks the heartbeat when your turn ends.
  • Exit code 100 is a planned checkpoint restart, not an error. Rerun the same command immediately; it resumes from committed state.json.
  • Exit code 1 on a non-empty error set is your turn. The loop exited because a task crashed; the script already wrote a synthetic handoffs/<task>-failure.md for each dead worker and any handoffs/<task>-finished-no-handoff.md for workers that ended without a structured handoff. In-flight workers keep running; the next run reattaches via recoverRunning.
  • After run returns, call tree. If any task is still pending or running, loop again.
  • Don't end your turn while this workspace has non-terminal tasks.

Reacting to failure handoffs: For each task with status: "error" and a matching handoffs/<task>-failure.md, read the Failure mode line and decide:

  • cap-hit or oom: retry with smaller scope (split into narrower tasks, tighter pathsAllowed, leaner scopedGoal).
  • network-drop: retry as-is; treat as transient.
  • tool-error: retry with a different model.
  • unknown: read the Last activity and SDK error lines; if no signal, treat as transient and retry as-is; abandon if it fails again. For <task>-finished-no-handoff.md, read the raw snippet at handoffs/<task>.md and decide whether the worker's intent was recoverable; retry or abandon. Each retry costs another cloud-agent run; budget your decisions. After 2 retries on the same task, prefer abandon (drop the task from plan.json, replan around it) over a 3rd attempt unless you have specific evidence the next retry will succeed. Update plan.json, then re-run bun cli.ts run{{rootFlag}} <workspace> to continue.

Source: SKILL.md on GitHub

2 warnings16d3 checks · Risk MEDIUM
  • Gen Agent Trust Hub16d

    The skill is a robust orchestration framework for parallel AI agents with significant built-in security controls, including automated redaction and environment isolation. However, it exposes a local command execution surface through its measurements feature and has a vulnerability surface for indirect prompt injection when interpolating agent handoffs.

  • Socket16d

    1 alert: gptSecurity

  • Snyk16d

    Risk: LOW · No issues

Signed by skilld at 03192a5. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 5 months ago
disable-model-invocation
true

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