# runvouch

> runvouch — runvouch-runvouch. Use this tool when you need to ensure unattended AI agents operate within predefined limits and parameters. Runvouch solves problems of uncontrolled costs, unexpected outcomes, and lack of monitoring by implementing a dead man's switch, cost cap, and outcome check for AI workflows. It integrates with tools like Claude Code, OpenClaw, n8n, and cron, providing a secure interface for inputs and outputs.

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

## Description

Dead man's switch, cost cap and outcome check for unattended AI agents (Claude Code, OpenClaw, n8n, cron)

## 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/runvouch/runvouch)

## 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": "runvouch-runvouch"
    }
  }
}
```

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