charon-fan/skill-router

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

Meta & Workflow

| Skill | Best For | |-------|----------| | skill-router | Finding and selecting the right skill for a task | | create-pr | Creating pull requests with bilingual documentation checks | | session-logger | Saving session summaries and activity logs | | workflow-orchestrator | Coordinating multi-skill workflows and triggers | | self-improving-agent | Learning from completed skill workflows | | auto-trigger | Declaring trigger relationships between skills |

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 |

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 | |-------|----------| | prd-planner | Creating PRDs with persistent file-based planning | | prd-implementation-precheck | Prechecking PRDs/specs before implementation | | architecting-solutions | Non-PRD solution design, architecture, and requirements analysis | | planning-with-files | Multi-step task planning, persistent file-based organization | | long-task-coordinator | Multi-session, delegated, or resumable work that needs explicit state and recovery |

Design & UX

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

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)