# nit

> nit — spaceparrots-nit. Use this tool when you need to quickly annotate and fix small UI issues on a website, and hand off the changes to a coding agent for implementation. It solves problems such as streamlining website iteration and reducing communication overhead between designers and developers. The tool takes in annotated website screenshots and outputs fixed code, with before/after verification via screenshots.

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

## Description

Point-and-click website annotation that hands small UI fixes straight to a coding agent. Annotate in a real browser, let the agent fix, verify with before/after screenshots.

## Trust

- **Trust score (0–1):** 0.59
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** AGPL-3.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/SpaceParrots/nit)

## 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": "spaceparrots-nit"
    }
  }
}
```

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