# roady

> roady — klarlabs-studio-roady. Use this tool when you need to manage and track AI coding projects with version control and change detection. It solves problems of context loss and project drift by providing a plan-of-record that survives context resets. The tool takes file-based inputs and outputs git-versioned plans, making it ideal for collaborative AI coding projects that require robust version control and change management.

Canonical page: https://skillsregistry.net/skills/klarlabs-studio-roady  
JSON: https://api.skillsregistry.net/v1/skills/klarlabs-studio-roady

## Description

The plan-of-record for AI coding agents — spec, plan, and drift detection that survive context resets. File-based, git-versioned, MCP-native.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** MIT
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/klarlabs-studio/roady)

## 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": "klarlabs-studio-roady"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/klarlabs-studio-roady` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/klarlabs-studio-roady/pull`

---
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