# FastHands

> FastHands — tomaszteee-fasthands. Use this tool when you need to execute and manage AI workflows locally across multiple platforms with durable checkpoints and operator control. FastHands solves problems of inconsistent AI performance, lack of control, and limited research capabilities by providing a reliable and flexible execution layer. It accepts git-based inputs and outputs research results, making it ideal for AI development and research contexts.

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

## Description

Local-first cross-platform execution and research layer for AI agents with durable checkpoints and operator control.

## Trust

- **Trust score (0–1):** 0.42
- **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/tomaszteee/FastHands)

## 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": "tomaszteee-fasthands"
    }
  }
}
```

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