# workrail

> workrail — etiennebbeaulac-workrail. Use this tool when you need to enforce structured workflows and ensure AI agents like Claude follow step-by-step tasks without deviations. Workrail solves problems of skipped steps and corner-cutting by guiding agents through predefined workflows, taking input from git repositories and outputting compliant task executions. It is ideal for use cases requiring rigorous adherence to protocols and standards.

Canonical page: https://skillsregistry.net/skills/etiennebbeaulac-workrail  
JSON: https://api.skillsregistry.net/v1/skills/etiennebbeaulac-workrail

## Description

MCP workflow enforcement server -- guides Claude and other AI agents through structured, step-by-step tasks without skipping steps or cutting corners

## 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:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/EtienneBBeaulac/workrail)

## 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": "etiennebbeaulac-workrail"
    }
  }
}
```

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