An intelligent router that analyzes user requests and recommends the most appropriate Claude Code skill for the task.
When This Skill Activates
This skill activates when you:
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Ask "which skill should I use?" or "what skill can help with...?"
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Say "use a skill" without specifying which one
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Express a need but aren't sure which skill fits
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Mention "skill router" or "help me find a skill"
Available Skills Catalog
Core Development
| commit-helper
| Writing Git commit messages, formatting commits
| code-reviewer
| Reviewing PRs, code changes, quality checks
| debugger
| Diagnosing bugs, errors, unexpected behavior
| refactoring-specialist
| Improving code structure, reducing technical debt
Design & UX
| figma-designer
| Analyzing Figma designs and producing implementation-ready visual specs/PRDs
Documentation & Testing
| documentation-engineer
| Writing README, technical docs, code documentation
| api-documenter
| Creating OpenAPI/Swagger specifications
| test-automator
| Writing tests, setting up test frameworks
| qa-expert
| Test strategy, quality gates, QA processes
Architecture & DevOps
| api-designer
| Designing REST/GraphQL APIs, API architecture
| security-auditor
| Security audits, vulnerability reviews, OWASP Top 10
| performance-engineer
| Performance optimization, speed analysis
| deployment-engineer
| CI/CD pipelines, deployment automation
Planning & Analysis
| architecting-solutions
| Creating PRDs, solution design, requirements analysis
| planning-with-files
| Multi-step task planning, persistent file-based organization
| self-improving-agent
| Universal self-improvement that learns from all skill experiences
Routing Process
Step 1: Intent Analysis
Analyze the user's request to identify:
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Task Type: What does the user want to accomplish?
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Context: What is the working domain (web, mobile, data, etc.)?
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Complexity: Is this a simple task or complex workflow?
Step 2: Skill Matching
Match the identified intent to the most relevant skill(s) using:
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Keyword matching: Compare request keywords with skill descriptions
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Semantic similarity: Understand the meaning behind the request
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Context awareness: Consider project state and previous actions
Step 3: Interactive Clarification
If the request is ambiguous, guide the user with targeted questions:
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What is the primary goal?
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What type of output is expected?
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Are there specific constraints or preferences?
Step 4: Recommendation & Execution
Present the recommended skill with:
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Skill name and brief description
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Why it fits the current request
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Option to proceed or ask for alternatives
Routing Examples
Example 1: Clear Intent
User: "I need to review this pull request"
Router Analysis:
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Keywords: "review", "pull request"
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Intent: Code review
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Recommendation:
code-reviewer
Example 2: Ambiguous Intent
User: "Use a skill to help with my project"
Router Questions:
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What type of task are you working on?
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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:
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api-designer- Design the API structure -
api-documenter- Document endpoints with OpenAPI -
test-automator- Set up API tests -
code-reviewer- Review implementation
Interactive Question Templates
When user intent is unclear, use these question patterns:
Goal Clarification
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"What are you trying to accomplish with this task?"
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"What would the ideal outcome look like?"
Domain Identification
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"What area does this relate to: development, testing, documentation, or deployment?"
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"Are you working on code, APIs, infrastructure, or something else?"
Stage Assessment
- "What stage are you at: planning, implementing, testing, or maintaining?"
Preference Confirmation
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"Do you want a quick solution or a comprehensive approach?"
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"Are there specific tools or frameworks you're using?"
Best Practices
1. Start Broad, Then Narrow
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Begin with general category questions
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Drill down into specifics based on responses
2. Explain Your Reasoning
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Tell the user why a particular skill is recommended
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Build trust through transparency
3. Offer Alternatives
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Present the top recommendation
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Mention 1-2 alternatives if applicable
4. Handle Edge Cases
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If no skill fits perfectly, suggest the closest match
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Offer to help without a specific skill if better
5. Learn from Context
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Consider previous interactions
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Remember user preferences for future routing
Advanced Routing Patterns
Semantic Routing
Use semantic similarity when keywords don't match directly:
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"clean up my code" →
refactoring-specialist -
"make my app faster" →
performance-engineer -
"check for security issues" →
security-auditor
Multi-Skill Orchestrations
Suggest skill combinations for complex workflows:
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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:
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High: Direct keyword match, clear intent
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Medium: Semantic similarity, reasonable inference
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Low: Ambiguous request, clarification needed
Error Recovery
If the recommended skill doesn't fit:
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Acknowledge the mismatch
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Ask follow-up questions to refine understanding
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Provide alternative recommendations
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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?