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name: launch-a-swarm description: Spawn 5 parallel agents applying quality principles across planning, building, and validating code. Use when designing features, making decisions, or checking work. Triggers on "launch a swarm" or when ensuring solid, maintainable, secure software.

Launch A Swarm

TL;DR

Say "launch a swarm" to spawn 5 parallel agents that review your work through Structure, Protection, Correctness, Evolution, and Value lenses. Use during planning, building, or validation phases.

What This Does

Spawns 5 specialized agents working in parallel to ensure your software is well-built across all critical dimensions. Think of it as having 5 experienced colleagues each examining your work from a different essential angle.

Why 5 domains? They cover the complete lifecycle of quality software without overlap:

• Structure catches organizational issues
• Protection prevents security/safety problems
• Correctness ensures things work right
• Evolution enables future changes
• Value keeps focus on what matters

When To Use

Say "launch a swarm" for comprehensive quality checks:

• Planning: Designing features, choosing technologies, making architectural decisions
• Building: Writing code and want real-time quality guidance
• Validating: Checking work before merge or deploy

When NOT to use:

• Simple, single-file changes with clear requirements
• Emergencies requiring immediate fixes (use after the fix)
• When you just need one perspective (call that specific agent directly)

The 5 Fundamental Domains

1. STRUCTURE (How It's Built)

Single source of truth. Independent parts. Clear organization.

Checks:

• Is knowledge in exactly one place? (DRY)
• Are components independent? (can change one without breaking others)
• Do parts know only what they must? (minimal coupling)
• Are names clear and meaningful?
• Is code organized logically?

2. PROTECTION (Keeping Bad Things Out)

Isolated. Validated. Defended.

Checks:

• Are services isolated in containers? (database, app, cache, web server separated)
• Is input validated before use? (never trust outside data)
• Does each part have minimum access needed? (least privilege)
• Are assumptions checked with assertions?
• Is attack surface minimized?
• Are secrets properly protected? (API keys, passwords)
• Are authentication and authorization enforced?
• Are resources cleaned up? (connections, files, memory)

3. CORRECTNESS (Does It Work Right?)

Tested. Validated. Reliable.

Checks:

• Is everything tested? (unit, integration, E2E, edge cases)
• Does data flow cleanly? (input → transform → output)
• Is state managed properly? (passed around, not shared globally)
• Do errors fail loudly? (crash early vs. limping along)
• Are edge cases handled?
• Is both happy path AND failure path tested?

4. EVOLUTION (Can It Change?)

Flexible. Configurable. Adaptable.

Checks:

• Will changes be localized or ripple everywhere?
• Is configuration external to code? (environment variables, not hardcoded)
• Can we swap implementations easily?
• Are decisions reversible?
• Is code rigid or flexible?
• Can we refactor without fear?

5. VALUE (Does It Matter?)

Solves problems. Ships fast. Documented.

Checks:

• Does this solve actual user need?
• Is build/test/deploy automated?
• Is documentation current and useful?
• Are we shipping or just coding?
• Is it simple or over-engineered?
• Can we deliver when users need it?

How It Works

Step 1: Understand Context

Before spawning agents, determine:

• What the user is working on
• The phase (planning, building, or validating)
• What files/areas are relevant

Phase Detection & Focus:

Step 2: Spawn 5 Agents in Parallel

Launch all 5 agents simultaneously using the Task tool:

CopyTask(
  description: "[Domain] Agent: Review [feature]",
  prompt: "[Agent prompt with context]",
  subagent_type: "general-purpose",
  run_in_background: true
)

Step 3: Synthesize Results

After all agents complete, combine findings using the output template below.

Agent Prompts

Each agent receives a self-contained prompt with embedded checks. Copy the full prompt—agents can't access other sections.

Base Template

CopyYou are the [DOMAIN] Agent.

[EMBED CHECKS FROM DOMAIN SECTION ABOVE]

Phase: [PLANNING/BUILDING/VALIDATING]
Context: [What user is working on]
Files: [Relevant file paths]

Report findings as:
1. **Issues** (with file:line references)
2. **Recommendations** (specific actions)
3. **Positives** (what's done well)

Domain-Specific Prompts

Structure Agent - copy checks from "1. STRUCTURE" section above

Protection Agent - copy checks from "2. PROTECTION" section above, plus:

• Add severity (CRITICAL/HIGH/MEDIUM/LOW) to all issues
• Include XSS/CSRF/Injection vulnerability checks

Correctness Agent - copy checks from "3. CORRECTNESS" section above, plus:

• Verify test types: E2E (Playwright), Unit (Vitest), Integration, Accessibility (WCAG AA)

Evolution Agent - copy checks from "4. EVOLUTION" section above

Value Agent - copy checks from "5. VALUE" section above, plus:

• Flag outdated documentation in README.md

Important: The orchestrator must embed the full checks in each prompt. Agents cannot access this skill file—they only receive their prompt text.

Output Template

After all agents complete, synthesize results:

Copy# Swarm Review Results

## Summary
Phase: [PLANNING/BUILDING/VALIDATING]
Scope: [What was reviewed]
Overall: [1-sentence assessment]

## Critical Issues (Must Fix Before Ship)
| Issue | Domain | Location | Fix |
|-------|--------|----------|-----|
| [issue] | Protection | file.ts:42 | [specific action] |

## Important Issues (Should Fix)
| Issue | Domain | Location | Fix |
|-------|--------|----------|-----|
| [issue] | Structure | file.ts:78 | [specific action] |

## Improvements (Nice To Have)
- [improvement] - [domain] - [location]

## Positive Patterns
- [what's working well] - [domain]

## Next Steps
1. [prioritized action]
2. [prioritized action]
3. [prioritized action]

## Domain Scores
- Structure: [Good/Needs Work/Critical Issues]
- Protection: [Good/Needs Work/Critical Issues]
- Correctness: [Good/Needs Work/Critical Issues]
- Evolution: [Good/Needs Work/Critical Issues]
- Value: [Good/Needs Work/Critical Issues]

Error Handling

If an agent fails to respond:

• Skip that domain in synthesis
• Note which domains completed
• Recommend re-running failed domain separately

If synthesis exceeds token limits:

• Prioritize Critical issues first
• Summarize Important issues
• Link to individual agent outputs

If agents conflict:

• Protection Agent > all others (security is non-negotiable)
• Correctness Agent > Evolution Agent (working code > flexible code)
• Value Agent provides tiebreaker for non-security issues

Examples

Planning a feature:

CopyUser: "Need to add user notifications. Launch a swarm."

Result:
- Structure: Component boundaries for notification service
- Protection: Input validation, rate limiting, auth checks needed
- Correctness: How to test notification delivery
- Evolution: Config for different notification channels
- Value: Does this solve user's actual communication need?

Validating code:

CopyUser: "Just built the payment flow. Launch a swarm."

Result:
- Structure: Payment logic is DRY, well-organized (✓)
- Protection: CRITICAL - API keys hardcoded in payment.ts:47
- Correctness: Missing tests for refund edge cases
- Evolution: Payment gateway is swappable (✓)
- Value: Meets user requirements, ready after fixes

Next Steps:
1. Fix hardcoded API keys in payment.ts:47 (Critical)
2. Add refund edge case tests
3. Update README.md with payment flow docs

Glossary

Container/Sandbox: Each service runs in isolation - if one is compromised, others stay protected Input Validation: Checking that data from users or APIs is safe before using it Attack Surface: The parts of your system exposed to potential attackers Secrets Management: Protecting API keys, passwords, and tokens from exposure DRY: Don't Repeat Yourself - knowledge in exactly one place Coupling: How much components depend on each other's internals Least Privilege: Giving each part only the minimum access it needs

Success Looks Like

Good Planning: Clear boundaries, isolated services, testable design, flexible architecture, solves real user need

Good Building: Principles applied as you write, no shortcuts accumulating, tests growing with code, input validated, configuration external

Good Validation: No critical issues, components decoupled and sandboxed, changes localized, tests passing, automated deployment, documentation current, you're proud to ship it

Remember

• Swarm adapts to what you're doing - planning gets different checks than validation
• Focus is improvement and partnership, not criticism
• Concrete guidance beats abstract principles
• Catching issues in planning is 10x easier than fixing in production
• Quality compounds - small good decisions add up to great software
• You build better when you know someone's checking your work