# looksy

> looksy — atre-looksy. Use this tool when you need to capture and analyze web pages from the command line, generating screenshots and metadata for accessibility audits, visual regression testing, and performance analysis. It solves problems related to web development, testing, and optimization, providing valuable insights for AI-assisted development. The tool takes URLs as input and outputs screenshots with accompanying metadata and analysis results.

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

## Description

Screenshot any URL from the command line with metadata sidecars, accessibility audits, visual regression, performance analysis, and MCP integration for AI-assisted development.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-29

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** api-integration
- **Updated:** 2026-08-29

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/m78qh5oiws)
- **Repository:** <https://github.com/atre/looksy>

## 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": "atre-looksy"
    }
  }
}
```

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

---
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