# routewise

> Use this tool when you need to optimize AI workflow execution by breaking down complex tasks into manageable steps and selecting the most suitable models within given constraints. Routewise solves problems of inefficient workflow management and model selection, providing a transparent execution process with full tracing capabilities. It takes in workflow tasks and constraints as inputs and outputs optimized execution plans with detailed traces.

Canonical page: https://skillsregistry.net/skills/bhavarth7-routewise  
JSON: https://api.skillsregistry.net/v1/skills/bhavarth7-routewise

## Description

Enables step-level routing of AI workflows by decomposing tasks, selecting the best model per step within constraints, executing steps, and providing full execution traces.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** productivity
- **Updated:** 2026-09-01

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/clrfp62adj)
- **Repository:** <https://github.com/Bhavarth7/RouteWise>

## 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": "bhavarth7-routewise"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/bhavarth7-routewise` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/bhavarth7-routewise/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