| name | orchestrate |
| description | 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. |
| disable-model-invocation | true |
Orchestrate
An explicit /orchestrate <goal> fans out a large task across parallel Cursor cloud agents. Workers don't talk to each other; they talk up through structured handoffs. The spawn, wait, and handoff loop lives in scripts/cli.ts. The planner writes plan.json, the script executes it, and the planner reads handoffs to decide what comes next. Long-running agent loops drift; a script with a JSON state file keeps its footing.
Required reading: the cursor-sdk skill (cursor/plugins/cursor-sdk). Spawning, auth, and the error taxonomy live there. Don't reimplement what that skill already documents.
Setup
CURSOR_API_KEY must be a personal/user key. Create it from Cursor Dashboard > Integrations, then read cursor-sdk Auth before using it.SLACK_BOT_TOKEN is optional. When set, pass --slack-channel <id> to kickoff or the first run --root, or set SLACK_CHANNEL_ID. The script stores the channel in plan.slackChannel, posts the kickoff thread there, mirrors task status, and reads Andon reactions. When the token is unset, the script logs once and runs without Slack visibility; correctness does not change.
Core principles
These rules make the tree self-converging without global coordination.
- Planners own scopes and publish tasks. They do no coding. Writing
plan.json, reading handoffs, and deciding what's next are planner work. Editing files, running git merge, and fixing conflicts inline are not. If a planner feels the urge to code, it publishes a task for a worker instead.
- Planners don't know who picks up their tasks. The script routes each task to a cloud agent. The planner's mental model stays at the task level.
- Workers are isolated. One task, one clone of the repo, no channel to any other agent. One handoff when done.
- Subplanners are recursive planners. A planner publishes a "subplan this slice" task; the subplanner fully owns that slice and hands back an aggregated handoff.
- Continuous motion via handoffs. A planner that thought it was done can receive a late handoff and replan. No "finished" state until the planner decides to stop publishing.
- Propagation, not synchronization. No cross-talk between siblings. No shared state between levels. Each level sees only its children's handoffs.
Node types
| Node | Runs the loop? | Scope | Output |
|---|
| Planner | yes | Entire user goal | User-facing message + optional PR |
| Subplanner (↻) | yes | One slice of parent's scope | Handoff to parent |
| Worker | no | One concrete task | Handoff to spawning planner |
| Verifier | no | One target's acceptance criteria | Verdict handoff to spawning planner |
| Git | n/a | Shared medium | Branches (code) + handoffs/ (meaning) |
Role
Two roles, one skill. Read your role's reference file and skip the other.
Dispatcher. You're in a local IDE session and the user typed /orchestrate <goal>. Your job is to kick off a cloud root planner and return its URL. See references/dispatcher.md. One-shot; you are not the planner.
Planner (root or sub). You were spawned with a structured prompt that opens with "You are the root planner for:" or "You are a subplanner for:". Or the user chose to run the planning loop locally. You own a scope, publish tasks, read handoffs, decide what's next. See references/planner.md.
disable-model-invocation: true means this skill loads only on explicit invocation.
