| name | openup-orchestrate |
| description | Run a full orchestrated iteration — PM decomposes the goal, delegates to specialist roles, collects outputs, and synthesizes results |
| model | inherit |
| fit | {"great":["complex multi-role tasks","architecture+impl+test cycles","anything benefiting from role isolation"],"ok":["medium tasks where decomposition aids token-efficiency"],"poor":["trivial changes","single-role work","hotfixes — heavyweight overkill"]} |
| arguments | [{"name":"task_id","description":"The task ID to orchestrate (must match a task in docs/roadmap.md)","required":true},{"name":"team","description":"Team type to use (feature, construction, elaboration, inception, transition, investigation, planning, full). Auto-selected from phase if not provided.","required":false},{"name":"dry_run","description":"Preview the orchestration plan without spawning teammates (true/false, default: false)","required":false}] |
Orchestrate Iteration
The Project Manager orchestrates a full iteration by decomposing the goal into role-specific subtasks, delegating to specialist teammates, collecting their outputs, and synthesizing a coherent result.
This skill implements the coordinator + specialist pattern: the PM acts as an orchestrator (coordinator) that spawns focused agents (specialists) with isolated task contexts, then integrates their outputs.
Prerequisites
- Iteration must already be initialized via
/openup-start-iteration
- Feature branch must be active (
git rev-parse --abbrev-ref HEAD returns a non-trunk branch)
docs/iteration-plan.md must exist with the iteration goal and acceptance criteria
Process
1. Load Iteration Context
Read the following (in order):
docs/iteration-plan.md — iteration goal, acceptance criteria, task listdocs/project-status.md — current phase, active taskdocs/roadmap.md — task details for $ARGUMENTS[task_id].claude/memory/iteration-learnings.md — past learnings to avoid repeating mistakes
2. Decompose Goal into Role Subtasks
Analyze the iteration goal and break it down by role. For each role in the active team, determine:
- What this role needs to contribute to achieve the iteration goal
- What context this role specifically needs (not the full project — just what's relevant)
- What deliverable this role should produce (specific document, code, decision, test)
- What "done" looks like for this role (criteria from the relevant rubric if applicable)
Document the decomposition before spawning any teammates:
Orchestration Plan for [task_id]:
Analyst: [subtask] → Deliverable: [output] → Done when: [criteria]
Architect: [subtask] → Deliverable: [output] → Done when: [criteria]
Developer: [subtask] → Deliverable: [output] → Done when: [criteria]
Tester: [subtask] → Deliverable: [output] → Done when: [criteria]
If $ARGUMENTS[dry_run] is true: output this plan and stop. Do not spawn teammates.
3. Select and Spawn Team
If team is not already active, determine the team type:
- Use
$ARGUMENTS[team] if provided
- Otherwise auto-select based on phase (same logic as
/openup-start-iteration step 7)
Spawn only the roles needed for this iteration's decomposition. Do not spawn roles that have no meaningful contribution to this specific task.
4. Brief Each Specialist
Send each teammate a focused brief using the PM's delegation format:
[ROLE]: Your task for this iteration is: [focused scope].
Context you need:
- [specific doc 1 with path]
- [specific doc 2 with path]
- [constraint or decision that affects their work]
Deliverable: [specific output — section of a document, code changes, test results]
Done when:
- [criterion 1]
- [criterion 2]
- [criterion 3]
Key rule: Give each specialist only the context they need. Do not dump the full project into every brief.
5. Collect Specialist Outputs
As each specialist completes their work, collect:
- Their deliverable (document, code, test results, recommendation)
- Any blockers or dependencies they identified
- Any decisions that require PM or cross-role coordination
Check each output against the "done when" criteria from their brief. If criteria are not met, send a follow-up brief with specific gaps to address.
6. Synthesize Results
Integrate all specialist outputs:
- Merge document contributions (architecture decisions + implementation + test coverage)
- Resolve any conflicts between specialist recommendations
- Verify the combined output satisfies the iteration acceptance criteria from
docs/iteration-plan.md
- Run
/openup-assess-completeness scope: iteration to get a final rubric-based assessment
If the assessment returns needs_revision: identify which specialist needs to address which gaps, and send targeted follow-up briefs (back to step 4 for the relevant role).
7. Save Orchestration Learnings
Append to .claude/memory/iteration-learnings.md:
## [YYYY-MM-DD] [task_id]: [task title] — Orchestrated
- **Team composition**: [roles used and why]
- **Delegation that worked well**: [what made a particular brief effective]
- **Coordination overhead**: [where handoffs created friction and how to avoid next time]
- **Synthesis challenges**: [conflicts between specialist outputs and how resolved]
8. Hand Off to Complete Task
Once all acceptance criteria are met and the rubric assessment is satisfied, invoke /openup-complete-task task_id: $ARGUMENTS[task_id] to commit, log, and create the PR.
Output
Returns:
- Orchestration plan (role → subtask → deliverable mapping)
- Per-specialist status (delivered / needs revision)
- Synthesis result (acceptance criteria met / gaps remaining)
- Final assessment result (satisfied / needs_revision)
See Also
