| name | vg-master-orchestrator |
| description | Master Orchestrator for autonomous multi-agent coordination. Use when tasks require multiple technology experts, complex workflows (TDD pattern addition, security audits), intelligent routing, or explicit orchestration requests. Coordinates 17 technology experts with real-time progress reporting. |
| version | 2.0.0 |
| allowed-tools | Read, Write, Edit, Bash, Grep, Glob, Task, SlashCommand, Skill |
Master Orchestrator - Execution Instructions (v2.0.0)
Purpose
Execute autonomous multi-agent coordination for Vigil Guard v2.0.0 tasks. Analyze, classify, route to technology experts, and synthesize results.
Quick Reference
Architecture: 3-Branch Parallel Detection (24 nodes)
Available experts: 17 technology experts in .claude/agents/
Full details: See CLAUDE.md section "Technology Expert Agents (v3.0)"
Technology Experts (17)
| Expert | Technology | Use For |
|---|---|---|
orchestrator |
Coordination | Multi-expert task routing |
n8n-expert |
n8n | Workflows, nodes, webhooks |
react-expert |
React + Vite | Components, hooks, UI |
express-expert |
Express.js | REST APIs, middleware |
vitest-expert |
Vitest | Testing, TDD, fixtures |
clickhouse-expert |
ClickHouse | Analytics SQL, schema |
docker-expert |
Docker | Containers, compose (11 services) |
presidio-expert |
MS Presidio | PII detection, NLP |
security-expert |
Security | OWASP, auth, vulnerabilities |
git-expert |
Git | Version control, commits |
python-expert |
Python | Flask, FastAPI |
tailwind-expert |
Tailwind CSS | Styling |
kubernetes-expert |
Kubernetes | Cluster ops, pods, deployments |
helm-expert |
Helm | Charts, releases, templating |
nats-expert |
NATS | Messaging, JetStream (future) |
redis-expert |
Redis | Caching, rate limiting (future) |
code-audit-expert |
Code Auditing | Quality assessment, tech debt |
v2.0.0 Architecture Context
3-Branch Parallel Detection System
Input → Validate → Config Load
↓
3-Branch Executor (PARALLEL):
├─ Branch A: Heuristics (:5005) - 30% weight
├─ Branch B: Semantic (:5006) - 35% weight
└─ Branch C: LLM Guard (:8000) - 35% weight
↓
Arbiter v2 (weighted fusion)
↓
Decision → PII Redaction → ClickHouse Log
Key Services (11 Docker containers)
vigil-heuristics(5005) - Pattern detectionvigil-semantic-service(5006) - Embedding similarityvigil-presidio-pii(5001) - PII detectionvigil-language-detector(5002) - Language detectionvigil-n8n(5678) - Workflow enginevigil-clickhouse(8123) - Analytics DBvigil-grafana(3001) - Monitoringweb-ui-backend(8787) - Config APIweb-ui-frontend(80) - React UIvigil-prompt-guard-api(8000) - LLM safetyvigil-caddy(80/443) - Reverse proxy
Execution Steps
1. Classify Task (Lightweight)
Determine strategy WITHOUT reading files:
- Single: One expert needed
- Parallel: Multiple independent experts
- Sequential: Experts depend on previous results
- Workflow: Matches pre-configured template
Workflows:
- PATTERN_ADDITION (TDD): vitest-expert → n8n-expert → vitest-expert
- SECURITY_AUDIT (Parallel): security-expert + vitest-expert + docker-expert
- PII_ENTITY_ADDITION: presidio-expert → express-expert → react-expert → vitest-expert
2. Execute with Progress Reporting
Format:
🎯 Task: [description]
🎭 Strategy: [single|parallel|sequential|workflow]
🤖 Expert: [name]-expert
├─ ▶️ Action: [action]
├─ 📝 [progress]
└─ ✅ Completed (X.Xs)
✨ Task Completed
3. Expert Invocation Methods
Option A - Use existing skill (FASTEST):
vigil-testing-e2efor testing tasksn8n-vigil-workflowfor workflow/pattern taskspresidio-pii-specialistfor PII tasksreact-tailwind-vigil-uifor UI tasksdocker-vigil-orchestrationfor container tasks- etc.
Option B - Task tool with technology expert:
Task(
prompt="You are n8n-expert. [task description]",
subagent_type="n8n-expert"
)
Option C - Direct implementation:
- Use Read/Write/Edit/Bash tools directly
- Only when no skill/expert available
4. Result Synthesis
═══════════════════════════════════════
✨ Task Completed in X.Xs
📋 Summary: [what was done]
🤝 Coordinated N experts:
• n8n-expert
• vitest-expert
💡 Next Steps:
1. [action 1]
2. [action 2]
Critical Rules
DO:
- ✅ Use existing skills when available (performance)
- ✅ Show real-time progress with emoji indicators
- ✅ Keep skill operations lightweight
- ✅ Reference v2.0.0 architecture (3-branch parallel, 24 nodes)
- ✅ Synthesize results concisely
DON'T:
- ❌ Reference old vg-* agents (REMOVED in v3.0)
- ❌ Reference 40-node sequential pipeline (NOW 24-node parallel)
- ❌ Reference rules.config.json (MERGED into unified_config.json)
- ❌ Read
.claude/agents/*/AGENT.mdunless truly needed - ❌ Just show documentation (EXECUTE the work)
- ❌ Load unnecessary context
Token Optimization
Problem: This skill + CLAUDE.md can cause session hangs due to token overload.
Solution:
- Classify tasks WITHOUT reading files
- Use existing skills (they're already loaded)
- Only read AGENT.md if truly needed
- Keep progress reporting concise
Error Handling
If expert fails:
- Report error with expert name
- Retry once
- Suggest fallback expert
- Continue with remaining work if possible
Integration
Slash command: /vg-orchestrate [task] → invokes this skill
Direct: User can also invoke via @vg-master-orchestrator or Skill tool
Version History
- v2.0.0 (2025-12): Updated for 3-branch architecture, 17 technology experts
- v2.0.1 (legacy): 10 vg-* agents (DEPRECATED)
Ready to orchestrate!