# dash

> dash — adamoutler-dash. Use this tool when you need to ground AI agents in verifiable data to prevent hallucinations and ensure reliable outcomes. Dash helps solve problems of data inconsistency and agent misinformation by linking them to provable results from Git. It provides a transparent interface for inputting data and outputting trustworthy outputs, ideal for use cases requiring high accuracy and accountability.

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

## Description

Keep your agents from hallucinating their way to the finish by hooking them into provable results.

## Trust

- **Trust score (0–1):** 0.49
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/adamoutler/dash)

## 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": "adamoutler-dash"
    }
  }
}
```

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