# roady

> Use this tool when you need to manage and track AI coding projects with version control and drift detection. Roady solves problems of project planning, spec management, and context resets by providing a file-based, git-versioned, and MCP-native solution. It takes in project specs and plans as inputs and outputs detectable drift and version updates, ideal for use in collaborative AI coding environments.

Canonical page: https://skillsregistry.net/skills/felixgeelhaar-roady  
JSON: https://api.skillsregistry.net/v1/skills/felixgeelhaar-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):** 0.61
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** file-system
- **Updated:** 2026-09-02

## Source

- **Source listing:** [GitHub](https://github.com/felixgeelhaar/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": "felixgeelhaar-roady"
    }
  }
}
```

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