# Rams

> Rams — ai-rams-rams. Use this tool when you need to review and improve the quality of your UI code, as it analyzes and scores your code against 258 rules across 9 categories, providing concrete fixes to enhance usability and functionality. It solves problems related to UI code design, accessibility, and best practices, and accepts UI code as input, outputting a scored review with actionable recommendations. Ideal for use during the development and testing phases to ensure high-quality UI code.

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

## Description

Design review for UI code: 291 rules, scored 0-100 with fixes and git-applyable patches.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/ai.rams%2Frams)

## Use it

MCP endpoint published by the skill: `https://worker.rams.ai/mcp`

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": "ai-rams-rams"
    }
  }
}
```

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