Openclaw Smart Router

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name: smart-router user-invocable: true metadata: {"openclaw":{"emoji":"🎯","requires":{"bins":["node"]},"os":["darwin","linux","win32"]}}

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OpenClaw Smart Router

Save 30-50% on model costs through intelligent, automatic model selection.

What is it?

The first OpenClaw skill that automatically routes requests to optimal models based on complexity analysis and budget constraints. Stops you from wasting money on expensive models for simple tasks. Learns from your usage patterns and gets smarter over time.

Key Features

🎯 30-50% Cost Savings - Automatic model selection based on task complexity

🧠 Complexity Analysis - Scores tasks 0.0-1.0 and selects appropriate model

💰 Budget Awareness - Respects spending limits and cost targets

📊 Pattern Learning - Learns which models work best for your tasks

🔄 Multi-Provider - Works with Anthropic, OpenAI, Google, and more

💸 x402 Payments - Agents can pay for unlimited routing (0.5 USDT/month)

Free vs Pro Tier

Free Tier:

100 routing decisions per day

Automatic complexity analysis

Basic model selection

Cost tracking

Pro Tier (0.5 USDT/month):

Unlimited routing decisions

Advanced pattern learning

Custom routing rules

Detailed analytics and ROI tracking

Budget optimization

Installation

claw skill install openclaw-smart-router

Commands

# View routing stats
claw router stats
Analyze complexity
claw router analyze "Your task description..."
View routing history
claw router history --limit=10
Show cost savings
claw router savings
Open dashboard
claw router dashboard
Subscribe to Pro
claw router subscribe

How It Works

1. Intercepts requests - Hooks before each API call 2. Analyzes complexity - Scores task from 0.0 (simple) to 1.0 (expert) 3. Checks budget - Considers spending limits 4. Selects model - Chooses optimal model: - Simple (0.0-0.3) → Haiku/GPT-3.5 - Medium (0.3-0.6) → Sonnet/GPT-4-Turbo - Complex (0.6-0.8) → Opus/GPT-4 - Expert (0.8-1.0) → Opus/GPT-4 5. Routes request - Sends to selected model 6. Learns from result - Tracks success and adapts

Complexity Scoring

What makes a task complex?

Context length (more context = higher complexity)

Code presence (code analysis scores higher)

Error messages (debugging is complex)

Task type (writing < coding < reasoning < research)

Question complexity (multiple parts, nested logic)

Specificity (vague requests need stronger models)

Examples:

Simple (0.0-0.3) → Haiku:

"What's the current time?"

"Format this JSON"

"Fix typo in variable name"

Medium (0.3-0.6) → Sonnet:

"Refactor this class to use interfaces"

"Write unit tests for this function"

"Explain how React hooks work"

Complex (0.6-0.8) → Opus:

"Debug this multi-threaded race condition"

"Design a scalable caching strategy"

"Optimize this algorithm for performance"

Expert (0.8-1.0) → Opus:

"Design a distributed system architecture"

"Solve this novel algorithmic problem"

"Research and synthesize from multiple sources"

Use Cases

Reduce model costs by 30-50% automatically

Stop manually switching between models

Budget-aware routing for cost control

Learn optimal model selection from patterns

Track spending and ROI over time

Cost Savings Examples

Example 1: Development Work

Without Smart Router:
100 requests/day to Opus
$0.015 per request
Monthly: $45
With Smart Router:
30 requests to Haiku ($0.90)
50 requests to Sonnet ($7.50)
20 requests to Opus ($9.00)
Monthly: $17.40
Savings: $27.60/month (61%)

Example 2: Customer Support

Without Smart Router:
500 requests/day to GPT-4
Monthly: $300
With Smart Router:
400 to GPT-3.5 ($24)
80 to GPT-4-Turbo ($24)
20 to GPT-4 ($12)
Monthly: $60
Savings: $240/month (80%)

Agent Economy

Agents can autonomously evaluate if Pro tier is worth it:

Cost: 0.5 USDT/month

Value: Saves 30-50% on model costs

ROI: If saves >0.5 USDT/month, it pays for itself

Example ROI:

Agent making 100 requests/day:
Without router: $45/month
With router: $17.40/month
Savings: $27.60/month
Pro cost: $0.50/month
Net profit: $27.10/month
ROI: 5,420%

Economic rationale: If routing decisions save more than 0.5 USDT/month in model costs, Pro tier pays for itself. Agent can autonomously pay via x402 without human approval.

See AGENT-PAYMENTS.md for x402 integration details.

Pattern Learning

Smart Router learns from your usage:

Example Learning:

Pattern detected: "Debug Python errors"
History: Haiku failed 3 times, Sonnet succeeded 5 times
Learning: Always use Sonnet+ for Python debugging
Next time: "Debug this Python error..."
→ Automatically routes to Sonnet instead of Haiku

What it learns:

Task-based patterns (debugging, refactoring, writing)

Complexity patterns (what works at different levels)

Budget patterns (when to downgrade, when quality matters)

Provider patterns (which providers work best for your tasks)

Integration with Other Tools

Memory System

Stores routing patterns as persistent memories

Recalls successful model selections across sessions

Maximum learning efficiency

Context Optimizer

Combine for 60-80% total cost reduction

Compress context (40-60% token savings)

Route to cheaper model (30-50% cost savings)

Together = maximum efficiency

Cost Governor

Smart Router optimizes model selection

Cost Governor enforces hard spending limits

Together = maximum cost control

# Install full efficiency suite
claw skill install openclaw-memory
claw skill install openclaw-context-optimizer
claw skill install openclaw-smart-router

Privacy

All data stored locally in ~/.openclaw/openclaw-smart-router/

No external servers or telemetry

Routing happens locally (no API calls)

Open source - audit the code yourself

Dashboard

Access web UI at http://localhost:9093:

Real-time routing decisions

Complexity distribution chart

Model selection breakdown

Cost savings over time

ROI calculation

Pattern learning insights

Budget tracking

License status

ROI Tracking

Smart Router automatically calculates return on investment:

$ claw router savings
Cost Analysis (Last 30 Days)
────────────────────────────────
Routing decisions: 2,847
Average complexity: 0.45
Model distribution:
Haiku: 42% ($3.60)
Sonnet: 49% ($21.00)
Opus: 9% ($11.12)
Total actual cost: $35.72
Without Smart Router: $128.12
Savings: $92.40 (72%)
Pro cost: $0.50/month
Net profit: $91.90/month
ROI: 18,380% 🎉

Requirements

Node.js 18+

OpenClaw v2026.1.30+

OS: Windows, macOS, Linux

Optional: OpenClaw Memory System (recommended)

Optional: OpenClaw Context Optimizer (highly recommended)

API Reference

# Analyze complexity
POST /api/analyze
{
  "agent_wallet": "0x...",
  "query": "Task description...",
  "context_length": 1500
}
Response:
{
  "complexity": 0.65,
  "recommended_model": "claude-sonnet-4-5",
  "recommended_provider": "anthropic",
  "estimated_cost": 0.008,
  "reasoning": "Medium complexity code task"
}
Get routing stats
GET /api/stats?agent_wallet=0x...
Get savings analysis
GET /api/savings?agent_wallet=0x...
Get learned patterns
GET /api/patterns?agent_wallet=0x...
x402 payment endpoints
POST /api/x402/subscribe
POST /api/x402/verify
GET /api/x402/license/:wallet

Budget Awareness

Smart Router respects your spending limits:

Budget levels:

Per-request max ($0.50 default)

Daily limit ($5.00 default)

Monthly limit ($100.00 default)

Budget strategies:

Conservative: Prefer cheaper models when viable

Balanced: Use recommended model, respect hard limits

Quality-First: Prioritize best model, soft budget constraints

Budget constraint handling:

IF daily_limit_reached:
  → Downgrade to cheapest viable model
  → Warn user about constraint
  → Log budget event

Supported Models

Anthropic:

claude-haiku-4-5 (simple)

claude-sonnet-4-5 (medium)

claude-opus-4-5 (complex)

OpenAI:

gpt-3.5-turbo (simple)

gpt-4-turbo (medium)

gpt-4 (complex)

Google:

gemini-1.5-flash (simple)

gemini-1.5-pro (medium/complex)

Custom providers:

Easily configure your own models and costs

Statistics Example

Smart Router Stats (30 Days)
────────────────────────────────
Total decisions: 2,847
Avg complexity: 0.45
Complexity breakdown:
Simple (0.0-0.3): 42%
Medium (0.3-0.6): 37%
Complex (0.6-0.8): 15%
Expert (0.8-1.0): 6%
Model distribution:
Haiku: 1,200 (42%)
Sonnet: 1,400 (49%)
Opus: 247 (9%)
Cost: $35.72 (vs $128.12 without)
Savings: 72% ($92.40/month)
Pattern learning:
23 patterns identified
94% success rate
342 pattern applications

Economic Rationale

Should you upgrade to Pro?

Calculate your potential savings:

Current requests/day × Avg cost per request = Monthly cost
Apply 30-50% savings = Amount saved
If saved amount > 0.5 USDT/month → Pro pays for itself

Typical savings:

Light usage (10-20 req/day): $3-8/month → $2.50-7.50 profit

Medium usage (50-100 req/day): $20-45/month → $19.50-44.50 profit

Heavy usage (200+ req/day): $100+/month → $99.50+ profit

ROI gets better with scale.

Links

Full Documentation

Routing Guide

Agent Payments Guide

GitHub Repository

ClawHub Page

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Built by the OpenClaw community | First smart model router with x402 payments