smart-routing

Intelligent routing engine for the /toh smart command. Routes any natural language request to the right agent(s).

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Install skill "smart-routing" with this command: npx skills add wasintoh/toh-framework/wasintoh-toh-framework-smart-routing

Smart Routing Skill

Intelligent routing engine for the /toh smart command. Routes any natural language request to the right agent(s).

🧠 Routing Pipeline

┌─────────────────────────────────────────────────────────────────┐ │ USER REQUEST │ ├─────────────────────────────────────────────────────────────────┤ │ │ │ STEP 0: MEMORY CHECK (ALWAYS FIRST!) │ │ ├── Read .toh/memory/active.md │ │ ├── Read .toh/memory/summary.md │ │ ├── Read .toh/memory/decisions.md │ │ └── Build context understanding │ │ │ │ STEP 1: INTENT CLASSIFICATION │ │ ├── Pattern matching (keywords, phrases) │ │ ├── Context inference (from memory) │ │ └── Scope detection (simple/complex) │ │ │ │ STEP 2: CONFIDENCE SCORING │ │ ├── HIGH (80%+) → Direct execution │ │ ├── MEDIUM (50-80%) → Plan Agent first │ │ └── LOW (<50%) → Ask for clarification │ │ │ │ STEP 3: IDE DETECTION │ │ ├── Claude Code → Parallel execution enabled │ │ └── Other IDEs → Sequential execution only │ │ │ │ STEP 4: AGENT SELECTION & EXECUTION │ │ └── Route to appropriate agent(s) │ │ │ └─────────────────────────────────────────────────────────────────┘

📊 Intent Classification Matrix

Primary Patterns → Agent Mapping

Pattern Category Keywords (EN) Keywords (TH) Primary Agent Confidence

Create UI create, add, make, build + page/component/UI สร้าง, เพิ่ม, ทำ + หน้า/component UI Agent HIGH

Add Logic logic, state, function, hook, validation logic, state, function, เพิ่ม logic Dev Agent HIGH

Fix Bug bug, error, broken, fix, not working bug, error, พัง, ไม่ทำงาน, แก้ Fix Agent HIGH

Improve Design prettier, beautiful, design, polish, style สวย, design, ปรับ design Design Agent HIGH

Testing test, check, verify test, ทดสอบ, เช็ค Test Agent HIGH

Connect Backend connect, database, Supabase, API, backend เชื่อม, database, Supabase Connect Agent HIGH

Deploy deploy, ship, production, publish deploy, ship, ขึ้น production Ship Agent HIGH

LINE Platform LINE, LIFF, Mini App LINE, LIFF LINE Agent HIGH

Mobile Platform mobile, iOS, Android, Expo, React Native mobile, มือถือ Mobile Agent HIGH

New Project new project, start, build app, create system project ใหม่, สร้าง app Vibe Agent HIGH

Planning plan, analyze, PRD, architecture วางแผน, วิเคราะห์ Plan Agent HIGH

AI/Prompt prompt, AI, chatbot, system prompt prompt, AI, chatbot Dev Agent + prompt-optimizer HIGH

Continue continue, resume, go on ทำต่อ, ต่อ Memory → Last Agent MEDIUM

Complex Request Multiple features, system, e-commerce, etc. ระบบ + หลาย features Plan Agent MEDIUM

Vague Request help, fix it, make better (without context) ช่วยด้วย, แก้ที Ask Clarification LOW

🎯 Confidence Scoring Algorithm

interface ConfidenceFactors { keywordMatch: number; // 0-40 points contextClarity: number; // 0-30 points memorySupport: number; // 0-20 points scopeDefinition: number; // 0-10 points }

function calculateConfidence(request: string, memory: Memory): number { let score = 0;

// Keyword matching (0-40 points) // Strong match with primary patterns = 40 // Partial match = 20 // No match = 0 score += keywordMatchScore(request);

// Context clarity (0-30 points) // Specific page/component mentioned = 30 // General area mentioned = 15 // No specifics = 0 score += contextClarityScore(request);

// Memory support (0-20 points) // Request relates to active task = 20 // Request relates to project = 10 // No memory context = 0 score += memorySupportScore(request, memory);

// Scope definition (0-10 points) // Single clear task = 10 // Multiple related tasks = 5 // Unclear scope = 0 score += scopeDefinitionScore(request);

return score; // 0-100 }

// Thresholds const HIGH_CONFIDENCE = 80; // Execute directly const MEDIUM_CONFIDENCE = 50; // Route to Plan Agent // Below 50 = Ask for clarification

🖥️ IDE Detection

Detection Method

function detectIDE(): 'claude-code' | 'cursor' | 'gemini' | 'codex' | 'unknown' { // Check for IDE-specific markers

// Claude Code detection if (hasClaudeCodeMarkers()) { return 'claude-code'; }

// Cursor detection if (hasCursorRules()) { return 'cursor'; }

// Gemini CLI detection if (hasGeminiConfig()) { return 'gemini'; }

// Codex CLI detection if (hasCodexConfig()) { return 'codex'; }

return 'unknown'; }

Execution Strategy by IDE

IDE Multi-Agent Strategy Reason

Claude Code Parallel (spawn sub-agents) Native support for parallel tool calls

Cursor Sequential More predictable, follows diff flow

Gemini CLI Sequential Safer execution model

Codex CLI Sequential Linear task processing

Unknown Sequential (default) Safe fallback

🔄 Routing Decision Tree

Request arrives │ ▼ ┌─────────────────────────────────────┐ │ 1. Load Memory Context │ └─────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────┐ │ 2. Is request "continue"/"ทำต่อ"? │ ├── YES → Read memory, resume task │ └── NO → Continue analysis │ │ ▼ ┌─────────────────────────────────────┐ │ 3. Calculate Confidence Score │ └─────────────────────────────────────┘ │ ├── Score >= 80 (HIGH) │ └─→ Select agent based on intent │ └─→ Execute directly │ ├── Score 50-79 (MEDIUM) │ └─→ Route to Plan Agent │ └─→ Plan Agent analyzes & routes │ └── Score < 50 (LOW) └─→ Ask clarifying question └─→ Wait for user response

📋 Clarification Patterns

When to Ask

Situation Example Action

No verb/action "the login" Ask: "What would you like to do with login?"

No target "make it work" Ask: "Which page/component should I fix?"

Multiple interpretations "improve it" Ask: "Design, performance, or features?"

Missing context + no memory "fix it" Ask: "What's broken? Describe the issue."

When NOT to Ask

Situation Example Action

Clear intent "create login page" Execute directly

Memory provides context "continue" + active task exists Resume from memory

Reasonable default exists "add a button" Add to current page context

🎨 Skill Loading by Intent

Detected Intent Skills to Load

New Project vibe-orchestrator, design-mastery, business-context, response-format

Create UI ui-first-builder, design-excellence, response-format

Add Logic dev-engineer, error-handling, response-format

Fix Bug debug-protocol, error-handling, response-format

Connect Backend backend-engineer, integrations, response-format

Improve Design design-excellence, design-mastery, response-format

AI/Chatbot prompt-optimizer, dev-engineer, response-format

Testing test-engineer, error-handling, response-format

Planning plan-orchestrator, business-context, response-format

Note: response-format skill is ALWAYS loaded for proper output formatting.

💾 Memory Integration

Pre-Routing Memory Check

Before routing, ALWAYS:

  1. Read .toh/memory/active.md

    • Current task context
    • In-progress work
    • Blockers
  2. Read .toh/memory/summary.md

    • Project overview
    • Completed features
    • Tech stack used
  3. Read .toh/memory/decisions.md

    • Past architectural decisions
    • Design choices
    • Naming conventions

Use memory to:

  • Boost confidence (if request matches active work)
  • Provide context (for ambiguous "it" references)
  • Maintain consistency (follow established patterns)

Post-Execution Memory Save

After routing completes, ALWAYS:

  1. Update .toh/memory/active.md

    • Mark completed items
    • Update current focus
    • Set next steps
  2. Add to .toh/memory/decisions.md

    • If new decisions were made
  3. Update .toh/memory/summary.md

    • If feature was completed

⚠️ NEVER finish without saving memory!

📌 Examples

Example 1: High Confidence → Direct

Request: "/toh สร้างหน้า dashboard"

Analysis:

  • Keyword match: "สร้าง" + "หน้า" = Create UI (40 pts)
  • Context clarity: "dashboard" = specific page (30 pts)
  • Memory: Project has other pages (15 pts)
  • Scope: Single page (10 pts) Total: 95 pts = HIGH

Route: UI Agent (direct)

Example 2: Medium Confidence → Plan First

Request: "/toh build e-commerce"

Analysis:

  • Keyword match: "build" = Create (40 pts)
  • Context clarity: "e-commerce" = general concept (10 pts)
  • Memory: New project (0 pts)
  • Scope: Multiple features (0 pts) Total: 50 pts = MEDIUM

Route: Plan Agent first → then execute plan

Example 3: Low Confidence → Ask

Request: "/toh fix it"

Analysis:

  • Keyword match: "fix" (20 pts)
  • Context clarity: "it" = unclear (0 pts)
  • Memory: No recent bugs (0 pts)
  • Scope: Unknown (0 pts) Total: 20 pts = LOW

Action: Ask "What would you like me to fix? Please describe the issue."

⚠️ Critical Rules

  • Memory ALWAYS first - Never route without checking context

  • Confidence drives action - Trust the scoring system

  • Plan Agent is your friend - When in doubt, route to Plan

  • IDE awareness matters - Parallel only in Claude Code

  • response-format always loaded - Every response needs 3 sections

Smart Routing Skill v1.0.0 - Intelligent Request Routing Engine

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