intelligent-routing
Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.
Best use case
intelligent-routing is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.
Teams using intelligent-routing should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/intelligent-routing/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How intelligent-routing Compares
| Feature / Agent | intelligent-routing | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Automatic agent selection and intelligent task routing. Analyzes user requests and automatically selects the best specialist agent(s) without requiring explicit user mentions.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 | ⚡ 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:
```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.Related Skills
routing-profiles
Change the Routing Solution routing profiles/vehicle types. To be used as part of customize-main skill
url-routing-patterns
Use when designing URL structures, slug generation, SEO-friendly URLs, redirects, or localized URL patterns. Covers route configuration, URL rewriting, canonical URLs, and routing APIs for headless CMS.
bgo
Automates the complete Blender build-go workflow, from building and packaging your extension/add-on to removing old versions, installing, enabling, and launching Blender for quick testing and iteration.
accessibility-ux-audit
Audit and enhance accessibility and UX across all pages and components.
accessibility-testing
WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.
accessibility-rules
Concise accessibility checklist and practices for components in the repository. Use when implementing UI to ensure keyboard, screen reader, and focus semantics.
accessibility-planning
Plan accessibility compliance - WCAG 2.2, Section 508, EN 301 549, inclusive design principles, audit planning, and remediation strategies.
accessibility-design
WCAG 2.1 AA compliance patterns, screen reader compatibility, keyboard navigation, and ARIA best practices. Use when implementing accessible interfaces, reviewing UI components, or auditing accessibility compliance. Covers semantic HTML, focus management, color contrast, and assistive technology testing.
accessibility-design-checklist
Эксперт по accessibility дизайну. Используй для WCAG, a11y чеклистов и inclusive design.
accessibility-design-checker
Ensures designs meet accessibility requirements including WCAG compliance, color contrast, keyboard navigation, screen reader support, and focus management. Reviews designs for accessibility issues and provides recommendations.
accessibility-contrast-audit
[Design System] Quantitative accessibility audit for UI - contrast ratios, font sizes, tap targets, heading hierarchy. Use when (1) checking WCAG color contrast compliance, (2) auditing text sizes for readability, (3) validating touch/click target sizes, (4) reviewing heading structure and landmarks, (5) user asks to 'check accessibility', 'audit contrast', 'WCAG compliance', or 'a11y check'.
accessibility-compliance
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns, and assistive technology support. Use when auditing accessibility, implementing ARIA patterns, building for screen readers, or ensuring inclusive user experiences.