# Send Openclaw Smart Router to your agent
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
## Fast path
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
## Suggested prompts
### New install

```text
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
```
### Upgrade existing

```text
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
```
## Machine-readable fields
```json
{
  "schemaVersion": "1.0",
  "item": {
    "slug": "openclaw-smart-router",
    "name": "Openclaw Smart Router",
    "source": "tencent",
    "type": "skill",
    "category": "AI 智能",
    "sourceUrl": "https://clawhub.ai/AtlasPA/openclaw-smart-router",
    "canonicalUrl": "https://clawhub.ai/AtlasPA/openclaw-smart-router",
    "targetPlatform": "OpenClaw"
  },
  "install": {
    "downloadUrl": "/downloads/openclaw-smart-router",
    "sourceDownloadUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=openclaw-smart-router",
    "sourcePlatform": "tencent",
    "targetPlatform": "OpenClaw",
    "packageFormat": "ZIP package",
    "primaryDoc": "SKILL.md",
    "includedAssets": [
      "API-REFERENCE.md",
      "DATABASE-IMPLEMENTATION.md",
      "hooks/provider-after.js",
      "hooks/request-before.js",
      "hooks/session-end.js",
      "IMPLEMENTATION.md"
    ],
    "downloadMode": "redirect",
    "sourceHealth": {
      "source": "tencent",
      "status": "healthy",
      "reason": "direct_download_ok",
      "recommendedAction": "download",
      "checkedAt": "2026-04-30T16:55:25.780Z",
      "expiresAt": "2026-05-07T16:55:25.780Z",
      "httpStatus": 200,
      "finalUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
      "contentType": "application/zip",
      "probeMethod": "head",
      "details": {
        "probeUrl": "https://wry-manatee-359.convex.site/api/v1/download?slug=network",
        "contentDisposition": "attachment; filename=\"network-1.0.0.zip\"",
        "redirectLocation": null,
        "bodySnippet": null
      },
      "scope": "source",
      "summary": "Source download looks usable.",
      "detail": "Yavira can redirect you to the upstream package for this source.",
      "primaryActionLabel": "Download for OpenClaw",
      "primaryActionHref": "/downloads/openclaw-smart-router"
    },
    "validation": {
      "installChecklist": [
        "Use the Yavira download entry.",
        "Review SKILL.md after the package is downloaded.",
        "Confirm the extracted package contains the expected setup assets."
      ],
      "postInstallChecks": [
        "Confirm the extracted package includes the expected docs or setup files.",
        "Validate the skill or prompts are available in your target agent workspace.",
        "Capture any manual follow-up steps the agent could not complete."
      ]
    }
  },
  "links": {
    "detailUrl": "https://openagent3.xyz/skills/openclaw-smart-router",
    "downloadUrl": "https://openagent3.xyz/downloads/openclaw-smart-router",
    "agentUrl": "https://openagent3.xyz/skills/openclaw-smart-router/agent",
    "manifestUrl": "https://openagent3.xyz/skills/openclaw-smart-router/agent.json",
    "briefUrl": "https://openagent3.xyz/skills/openclaw-smart-router/agent.md"
  }
}
```
## Documentation

### 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

Intercepts requests - Hooks before each API call
Analyzes complexity - Scores task from 0.0 (simple) to 1.0 (expert)
Checks budget - Considers spending limits
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


Routes request - Sends to selected model
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

### 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)

### 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

Built by the OpenClaw community | First smart model router with x402 payments
## Trust
- Source: tencent
- Verification: Indexed source record
- Publisher: AtlasPA
- Version: 1.0.0
## Source health
- Status: healthy
- Source download looks usable.
- Yavira can redirect you to the upstream package for this source.
- Health scope: source
- Reason: direct_download_ok
- Checked at: 2026-04-30T16:55:25.780Z
- Expires at: 2026-05-07T16:55:25.780Z
- Recommended action: Download for OpenClaw
## Links
- [Detail page](https://openagent3.xyz/skills/openclaw-smart-router)
- [Send to Agent page](https://openagent3.xyz/skills/openclaw-smart-router/agent)
- [JSON manifest](https://openagent3.xyz/skills/openclaw-smart-router/agent.json)
- [Markdown brief](https://openagent3.xyz/skills/openclaw-smart-router/agent.md)
- [Download page](https://openagent3.xyz/downloads/openclaw-smart-router)