# L4-Smartroute

> L4-Smartroute — linux5real-l4-smartroute. Use this tool when you need to optimize AI model selection for coding tasks, as it analyzes complexity and recommends the best model and effort level from 80+ models across 15+ providers. It solves problems of inefficient model choice and resource allocation, streamlining the development process. Input your task requirements and receive output recommendations for the most suitable AI model and effort level.

Canonical page: https://skillsregistry.net/skills/linux5real-l4-smartroute  
JSON: https://api.skillsregistry.net/v1/skills/linux5real-l4-smartroute

## Description

Intelligent AI model routing for coding agents. Analyzes task complexity using knowledge graphs to recommend the best AI model & effort level across 80+ models from 15+ providers.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/Linux5Real/L4-Smartroute)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "linux5real-l4-smartroute"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/linux5real-l4-smartroute` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/linux5real-l4-smartroute/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt