Skill Router

Skill Router

Analyze the request and recommend the narrowest matching skill exposed by the current host. Do not assume Claude Code, Codex, Gemini, or DeepSeek Harness capabilities that are not visible in the current session.

When This Skill Activates

This skill activates when you:

• Ask "which skill should I use?" or "what skill can help with...?"
• Say "use a skill" without specifying which one
• Express a need but aren't sure which skill fits
• Mention "skill router" or "help me find a skill"

Available Skills Catalog

Meta & Workflow

Core Development

Documentation & Testing

Architecture & DevOps

Planning & Analysis

Design & UX

Routing Process

Step 1: Intent Analysis

Analyze the user's request to identify:

• Task Type: What does the user want to accomplish?
• Context: What is the working domain (web, mobile, data, etc.)?
• Complexity: Is this a simple task or complex workflow?

Step 2: Skill Matching

Match the identified intent to the most relevant skill(s) using:

• Keyword matching: Compare request keywords with skill descriptions
• Semantic similarity: Understand the meaning behind the request
• Context awareness: Consider project state and previous actions

Step 3: Interactive Clarification

If the request is ambiguous, guide the user with targeted questions:

• What is the primary goal?
• What type of output is expected?
• Are there specific constraints or preferences?

Step 4: Recommendation & Execution

Present the recommended skill with:

• Skill name and brief description
• Why it fits the current request
• Option to proceed or ask for alternatives

Routing Examples

Example 1: Clear Intent

User: "I need to review this pull request"

Router Analysis:

• Keywords: "review", "pull request"
• Intent: Code review
• Recommendation: code-reviewer

Example 2: Ambiguous Intent

User: "Use a skill to help with my project"

Router Questions:

1. What type of task are you working on?
2. Are you designing, coding, testing, or documenting?

Based on answers → Recommend appropriate skill

Example 3: Multi-Skill Scenario

User: "I'm building a new API and need help with the full workflow"

Router Recommendation: Consider using multiple skills in sequence:

1. api-designer - Design the API structure
2. api-documenter - Document endpoints with OpenAPI
3. test-automator - Set up API tests
4. code-reviewer - Review implementation

Interactive Question Templates

When user intent is unclear, use these question patterns:

Goal Clarification

• "What are you trying to accomplish with this task?"
• "What would the ideal outcome look like?"

Domain Identification

• "What area does this relate to: development, testing, documentation, or deployment?"
• "Are you working on code, APIs, infrastructure, or something else?"

Stage Assessment

• "What stage are you at: planning, implementing, testing, or maintaining?"

Preference Confirmation

• "Do you want a quick solution or a comprehensive approach?"
• "Are there specific tools or frameworks you're using?"

Best Practices

1. Start Broad, Then Narrow

• Begin with general category questions
• Drill down into specifics based on responses

2. Explain Your Reasoning

• Tell the user why a particular skill is recommended
• Build trust through transparency

3. Offer Alternatives

• Present the top recommendation
• Mention 1-2 alternatives if applicable

4. Handle Edge Cases

• If no skill fits perfectly, suggest the closest match
• Offer to help without a specific skill if better

5. Learn from Context

• Consider previous interactions
• Remember user preferences for future routing

Advanced Routing Patterns

Semantic Routing

Use semantic similarity when keywords don't match directly:

• "clean up my code" → refactoring-specialist
• "make my app faster" → performance-engineer
• "check for security issues" → security-auditor
• "resume this interrupted workflow" → long-task-coordinator

Multi-Skill Orchestrations

Suggest skill combinations for complex workflows:

• New Feature: architecting-solutions → debugger → code-reviewer
• API Project: api-designer → api-documenter → test-automator
• Production Readiness: security-auditor → performance-engineer → deployment-engineer

Confidence Levels

Indicate confidence in recommendations:

• High: Direct keyword match, clear intent
• Medium: Semantic similarity, reasonable inference
• Low: Ambiguous request, clarification needed

Error Recovery

If the recommended skill doesn't fit:

1. Acknowledge the mismatch
2. Ask follow-up questions to refine understanding
3. Provide alternative recommendations
4. Fall back to general assistance if needed

Output Format

When recommending a skill, use this format:

## Recommended Skill: {skill-name}
{brief description of why this skill fits}
**What it does:** {one-sentence skill description}
**Best for:** {specific use cases}
---
Would you like me to activate this skill, or would you prefer to see other options?

References

• AI Agent Routing: Tutorial & Best Practices
• Intent Recognition and Auto-Routing in Multi-Agent Systems
• Multi-LLM Routing Strategies (AWS)