home / skills / willsigmon / sigstack / orchestrate-agents
This skill coordinates multi-agent workflows with handoffs and dependencies to streamline complex feature development across pipelines and reviews.
npx playbooks add skill willsigmon/sigstack --skill orchestrate-agentsReview the files below or copy the command above to add this skill to your agents.
---
name: Orchestrate Agents
description: Coordinate multi-agent workflows with handoffs and dependencies
allowed-tools: Task, TaskOutput, Read
model: sonnet
---
# Orchestrate Agents
**Complex workflows across multiple agents.**
## Orchestration Patterns
### Pipeline (Sequential)
```
Agent 1 → Agent 2 → Agent 3
Each depends on previous output.
Use for: Analysis → Design → Implementation
```
### Parallel + Merge
```
[Agent 1]
[Agent 2] → Merge → Final Agent
[Agent 3]
Independent work, combined results.
Use for: Multi-area search → Synthesis
```
### Supervisor
```
Supervisor Agent
├── Worker 1
├── Worker 2
└── Worker 3
Supervisor delegates and collects.
Use for: Complex features
```
### Specialist Ensemble
```
Security Agent ─┐
Performance Agent ─┼── Decision Agent
Style Agent ─────┘
Multiple perspectives, one decision.
Use for: Code review, architecture
```
## Dependency Management
### Sequential Dependencies
```
Can't parallelize:
1. Create model
2. Create view using model
3. Create tests for view
Run in order. No agents.
```
### Parallel Independence
```
Can parallelize:
1. Search auth/
2. Search payment/
3. Search user/
No dependencies. Spawn all.
```
### Partial Dependencies
```
[A, B, C] → D → [E, F]
A, B, C parallel
D waits for all
E, F parallel after D
```
## Handoff Protocol
### Agent to Agent
```
Agent 1 completes:
"Found issue in auth.swift:142"
You relay to Agent 2:
"Fix the issue in auth.swift:142"
Context transferred explicitly.
```
### Agent to Main
```
Agent returns summary.
You decide next action.
Main conversation has full control.
```
### Background Check-In
```
run_in_background: true
Later:
TaskOutput to check status
Resume if needed
```
## Complex Workflow Example
### Feature Implementation
```
Phase 1 (Parallel):
- Design agent: Plan the feature
- Research agent: Find similar patterns
Phase 2 (After Phase 1):
- Implementation agent: Build it
Phase 3 (Parallel):
- Test agent: Write tests
- Docs agent: Write documentation
Phase 4:
- Review agent: Final check
```
### Bug Investigation
```
Phase 1 (Parallel):
- Reproduce agent: Confirm the bug
- Search agent: Find related code
Phase 2:
- Analysis agent: Root cause
Phase 3:
- Fix agent: Implement solution
Phase 4 (Parallel):
- Test agent: Verify fix
- Regression agent: Check side effects
```
## Coordination Commands
### Start Workflow
```
"Start [workflow] for [target]"
Spawns appropriate agents.
Tracks progress.
```
### Check Progress
```
"Status of [workflow]?"
Shows:
- Completed steps
- In progress
- Blocked
- Next steps
```
### Adjust Workflow
```
"Skip [step]"
"Add [step] before [step]"
"Retry [step]"
```
## Error Handling
### Agent Fails
```
Agent hits error →
Report to main →
Decide: retry, skip, or abort
```
### Dependency Blocked
```
Blocker identified →
Create workaround or
Escalate for decision
```
### Timeout
```
Background agent too long →
Check with TaskOutput →
Decide: wait, cancel, or resume
```
## Best Practices
### ✓ Do
```
- Clear handoff messages
- Explicit dependencies
- Background for long work
- Check-in periodically
- Handle errors gracefully
```
### ❌ Don't
```
- Implicit dependencies
- Fire and forget
- Over-orchestrate simple tasks
- Ignore failures
```
Use when: Multi-step features, complex investigations, coordinated work
This skill coordinates multi-agent workflows with explicit handoffs, dependency management, and monitoring. It provides reusable orchestration patterns (pipeline, parallel + merge, supervisor, specialist ensemble) to organize agents for features, investigations, and operational tasks. The goal is predictable, auditable collaboration across agents so complex work completes reliably.
Define a workflow as phases and agents, declare dependencies, and spawn agents accordingly. The orchestrator routes context and handoff messages, tracks progress, and exposes control commands (start, status, adjust). Background tasks can check in and resume, while failures trigger retry, skip, or escalation rules.
How are dependencies declared?
Declare each agent's inputs and the steps that must complete before it runs; the orchestrator enforces order and parallelism.
What happens when an agent fails?
Failures are reported to the main controller; options are retry, skip, or abort. You can attach custom escalation rules.
Can agents run in the background?
Yes. Mark tasks run_in_background and use TaskOutput check-ins to resume or adjust based on status.