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.

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---
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

Overview

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.

How this skill works

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.

When to use it

  • Implementing multi-step features that require design, build, test, and review phases
  • Investigating bugs that need parallel reproduction, search, and analysis work
  • Coordinating specialists (security, performance, style) to reach a single decision
  • Running large searches or audits that can be parallelized and then merged
  • Managing long-running background tasks that need periodic check-ins

Best practices

  • Declare explicit dependencies so order and parallelism are clear
  • Send concise, explicit handoff messages with file/line and actionable instruction
  • Use background mode for long-running agents and schedule periodic status checks
  • Prefer supervisor or ensemble patterns for complex delegation and multi-perspective decisions
  • Handle failures proactively: report, decide (retry/skip/abort), and record rationale

Example use cases

  • Feature rollout: parallel design + research → implementation → parallel tests + docs → review
  • Bug triage: parallel reproduce + code search → root-cause analysis → fix → parallel tests/regression
  • Security review: run security specialist, performance specialist, and style specialist then merge findings into a decision
  • Large codebase search: spawn parallel search agents per module and synthesize results
  • Automated QA pipeline: sequential build → test → deploy with conditional retries on failure

FAQ

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.