| name | intelligent-routing |
| description | Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions. |
| version | 1.0.0 |
Intelligent Agent Routing
Purpose: Automatically analyze user requests and route them to the most appropriate specialist agent(s) without requiring explicit user mentions.
Core Principle
The AI should act as an intelligent Project Manager, analyzing each request and automatically selecting the best specialist(s) for the job.
How It Works
1. Request Analysis
Before responding to ANY user request, perform automatic analysis:
graph TD
A[User Request: Add login] --> B[ANALYZE]
B --> C[Keywords]
B --> D[Domains]
B --> E[Complexity]
C --> F[SELECT AGENT]
D --> F
E --> F
F --> G[security-auditor + backend-specialist]
G --> H[AUTO-INVOKE with context]
2. Agent Selection Matrix
Use this matrix to automatically select agents:
| User Intent | Keywords | Selected Agent(s) | Auto-invoke? |
|---|
| Authentication | "login", "auth", "signup", "password" | security-auditor + backend-specialist | ✅ YES |
| UI Component | "button", "card", "layout", "style" | frontend-specialist | ✅ YES |
| Mobile UI | "screen", "navigation", "touch", "gesture" | mobile-developer | ✅ YES |
| API Endpoint | "endpoint", "route", "API", "POST", "GET" | backend-specialist | ✅ YES |
| Database | "schema", "migration", "query", "table" | database-architect + backend-specialist | ✅ YES |
| Bug Fix | "error", "bug", "not working", "broken" | debugger | ✅ YES |
| Test | "test", "coverage", "unit", "e2e" | test-engineer | ✅ YES |
| Deployment | "deploy", "production", "CI/CD", "docker" | devops-engineer | ✅ YES |
| Security Review | "security", "vulnerability", "exploit" | security-auditor + penetration-tester | ✅ YES |
| Performance | "slow", "optimize", "performance", "speed" | performance-optimizer | ✅ YES |
| Product Def | "requirements", "user story", "backlog", "MVP" | product-owner | ✅ YES |
| New Feature | "build", "create", "implement", "new app" | orchestrator → multi-agent | ⚡ AUTO-PROCEED |
| Complex Task | Multiple domains detected | orchestrator → multi-agent | ⚡ AUTO-PROCEED |
3. Automatic Routing Protocol
TIER 0 - Automatic Analysis (ALWAYS ACTIVE)
Before responding to ANY request:
function analyzeRequest(userMessage) {
const requestType = classifyRequest(userMessage);
const domains = detectDomains(userMessage);
const complexity = assessComplexity(domains);
if (complexity === "SIMPLE" && domains.length === 1) {
return selectSingleAgent(domains[0]);
} else if (complexity === "MODERATE" && domains.length <= 2) {
return selectMultipleAgents(domains);
} else {
return "orchestrator";
}
}
4. Response Format
When auto-selecting an agent, inform the user concisely:
🤖 **Applying knowledge of `@security-auditor` + `@backend-specialist`...**
[Proceed with specialized response]
Benefits:
- ✅ User sees which expertise is being applied
- ✅ Transparent decision-making
- ✅ Still automatic (no /commands needed)
Domain Detection Rules
Single-Domain Tasks (Auto-invoke Single Agent)
| Domain | Patterns | Agent |
|---|
| Security | auth, login, jwt, password, hash, token | security-auditor |
| Frontend | component, react, vue, css, html, tailwind | frontend-specialist |
| Backend | api, server, express, fastapi, node | backend-specialist |
| Mobile | react native, flutter, ios, android, expo | mobile-developer |
| Database | prisma, sql, mongodb, schema, migration | database-architect |
| Testing | test, jest, vitest, playwright, cypress | test-engineer |
| DevOps | docker, kubernetes, ci/cd, pm2, nginx | devops-engineer |
| Debug | error, bug, crash, not working, issue | debugger |
| Performance | slow, lag, optimize, cache, performance | performance-optimizer |
| SEO | seo, meta, analytics, sitemap, robots | seo-specialist |
| Game | unity, godot, phaser, game, multiplayer | game-developer |
Multi-Domain Tasks (Auto-invoke Orchestrator)
If request matches 2+ domains from different categories, automatically use orchestrator:
Example: "Create a secure login system with dark mode UI"
→ Detected: Security + Frontend
→ Auto-invoke: orchestrator
→ Orchestrator will handle: security-auditor, frontend-specialist, test-engineer
Complexity Assessment
SIMPLE (Direct agent invocation)
- Single file edit
- Clear, specific task
- One domain only
- Example: "Fix the login button style"
Action: Auto-invoke respective agent
MODERATE (2-3 agents)
- 2-3 files affected
- Clear requirements
- 2 domains max
- Example: "Add API endpoint for user profile"
Action: Auto-invoke relevant agents sequentially
COMPLEX (Orchestrator required)
- Multiple files/domains
- Architectural decisions needed
- Unclear requirements
- Example: "Build a social media app"
Action: Auto-invoke orchestrator → will ask Socratic questions
Implementation Rules
Rule 1: Silent Analysis
DO NOT announce "I'm analyzing your request..."
- ✅ Analyze silently
- ✅ Inform which agent is being applied
- ❌ Avoid verbose meta-commentary
Rule 2: Inform Agent Selection
DO inform which expertise is being applied:
🤖 **Applying knowledge of `@frontend-specialist`...**
I will create the component with the following characteristics:
[Continue with specialized response]
Rule 3: Seamless Experience
The user should not notice a difference from talking to the right specialist directly.
Rule 4: Override Capability
User can still explicitly mention agents:
User: "Use @backend-specialist to review this"
→ Override auto-selection
→ Use explicitly mentioned agent
Edge Cases
Case 1: Generic Question
User: "How does React work?"
→ Type: QUESTION
→ No agent needed
→ Respond directly with explanation
Case 2: Extremely Vague Request
User: "Make it better"
→ Complexity: UNCLEAR
→ Action: Ask clarifying questions first
→ Then route to appropriate agent
Case 3: Contradictory Patterns
User: "Add mobile support to the web app"
→ Conflict: mobile vs web
→ Action: Ask: "Do you want responsive web or native mobile app?"
→ Then route accordingly
Integration with Existing Workflows
With /orchestrate Command
- User types
/orchestrate: Explicit orchestration mode
- AI detects complex task: Auto-invoke orchestrator (same result)
Difference: User doesn't need to know the command exists.
With Socratic Gate
- Auto-routing does NOT bypass Socratic Gate
- If task is unclear, still ask questions first
- Then route to appropriate agent
With GEMINI.md Rules
- Priority: GEMINI.md rules > intelligent-routing
- If GEMINI.md specifies explicit routing, follow it
- Intelligent routing is the DEFAULT when no explicit rule exists
Testing the System
Test Cases
Test 1: Simple Frontend Task
User: "Create a dark mode toggle button"
Expected: Auto-invoke frontend-specialist
Verify: Response shows "Using @frontend-specialist"
Test 2: Security Task
User: "Review the authentication flow for vulnerabilities"
Expected: Auto-invoke security-auditor
Verify: Security-focused analysis
Test 3: Complex Multi-Domain
User: "Build a chat application with real-time notifications"
Expected: Auto-invoke orchestrator
Verify: Multiple agents coordinated (backend, frontend, test)
Test 4: Bug Fix
User: "Login is not working, getting 401 error"
Expected: Auto-invoke debugger
Verify: Systematic debugging approach
Performance Considerations
Token Usage
- Analysis adds ~50-100 tokens per request
- Tradeoff: Better accuracy vs slight overhead
- Overall SAVES tokens by reducing back-and-forth
Response Time
- Analysis is instant (pattern matching)
- No additional API calls required
- Agent selection happens before first response
User Education
Optional: First-Time Explanation
If this is the first interaction in a project:
💡 **Tip**: I am configured with automatic specialist agent selection.
I will always choose the most suitable specialist for your task. You can
still mention agents explicitly with `@agent-name` if you prefer.
Debugging Agent Selection
Enable Debug Mode (for development)
Add to GEMINI.md temporarily:
## DEBUG: Intelligent Routing
Show selection reasoning:
- Detected domains: [list]
- Selected agent: [name]
- Reasoning: [why]
Summary
intelligent-routing skill enables:
✅ Zero-command operation (no need for /orchestrate)
✅ Automatic specialist selection based on request analysis
✅ Transparent communication of which expertise is being applied
✅ Seamless integration with existing workflows
✅ Override capability for explicit agent mentions
✅ Fallback to orchestrator for complex tasks
Result: User gets specialist-level responses without needing to know the system architecture.
Next Steps: Integrate this skill into GEMINI.md TIER 0 rules.
