Skill Router

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:

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

Core Development

Skill	Best For
`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

Skill	Best For
`figma-designer`	Analyzing Figma designs and producing implementation-ready visual specs/PRDs

Documentation & Testing

Skill	Best For
`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

Skill	Best For
`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

Skill	Best For
`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:

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:

What type of task are you working on?
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:

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

"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

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:

Acknowledge the mismatch
Ask follow-up questions to refine understanding
Provide alternative recommendations
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}

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Would you like me to activate this skill, or would you prefer to see other options?

skill-router