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:

mermaid

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	⚠️ ASK FIRST
Complex Task	Multiple domains detected	`orchestrator` → multi-agent	⚠️ ASK FIRST

3. Automatic Routing Protocol

TIER 0 - Automatic Analysis (ALWAYS ACTIVE)

Before responding to ANY request:

javascript

// Pseudo-code for decision tree
function analyzeRequest(userMessage) {
    // 1. Classify request type
    const requestType = classifyRequest(userMessage);

    // 2. Detect domains
    const domains = detectDomains(userMessage);

    // 3. Determine complexity
    const complexity = assessComplexity(domains);

    // 4. Select agent(s)
    if (complexity === "SIMPLE" && domains.length === 1) {
        return selectSingleAgent(domains[0]);
    } else if (complexity === "MODERATE" && domains.length <= 2) {
        return selectMultipleAgents(domains);
    } else {
        return "orchestrator"; // Complex task
    }
}

4. Response Format

When auto-selecting an agent, inform the user concisely:

markdown

🤖 **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

text

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:

markdown

🤖 **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:

text

User: "Use @backend-specialist to review this"
→ Override auto-selection
→ Use explicitly mentioned agent

Edge Cases

Case 1: Generic Question

text

User: "How does React work?"
→ Type: QUESTION
→ No agent needed
→ Respond directly with explanation

Case 2: Extremely Vague Request

text

User: "Make it better"
→ Complexity: UNCLEAR
→ Action: Ask clarifying questions first
→ Then route to appropriate agent

Case 3: Contradictory Patterns

text

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

text

User: "Create a dark mode toggle button"
Expected: Auto-invoke frontend-specialist
Verify: Response shows "Using @frontend-specialist"

Test 2: Security Task

text

User: "Review the authentication flow for vulnerabilities"
Expected: Auto-invoke security-auditor
Verify: Security-focused analysis

Test 3: Complex Multi-Domain

text

User: "Build a chat application with real-time notifications"
Expected: Auto-invoke orchestrator
Verify: Multiple agents coordinated (backend, frontend, test)

Test 4: Bug Fix

text

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:

markdown

💡 **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:

markdown

## 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.

intelligent-routing

NPX Install

Tags

SKILL.md Content

Intelligent Agent Routing

Core Principle

How It Works

1. Request Analysis

2. Agent Selection Matrix

3. Automatic Routing Protocol

TIER 0 - Automatic Analysis (ALWAYS ACTIVE)

4. Response Format

Domain Detection Rules

Single-Domain Tasks (Auto-invoke Single Agent)

Multi-Domain Tasks (Auto-invoke Orchestrator)

Complexity Assessment

SIMPLE (Direct agent invocation)

MODERATE (2-3 agents)

COMPLEX (Orchestrator required)

Implementation Rules

Rule 1: Silent Analysis

DO NOT announce "I'm analyzing your request..."

Rule 2: Inform Agent Selection

Rule 3: Seamless Experience

Rule 4: Override Capability

Edge Cases

Case 1: Generic Question

Case 2: Extremely Vague Request

Case 3: Contradictory Patterns

Integration with Existing Workflows

With /orchestrate Command

With Socratic Gate

With GEMINI.md Rules

Testing the System

Test Cases

Test 1: Simple Frontend Task

Test 2: Security Task

Test 3: Complex Multi-Domain

Test 4: Bug Fix

Performance Considerations

Token Usage

Response Time

User Education

Optional: First-Time Explanation

Debugging Agent Selection

Enable Debug Mode (for development)

Summary