# DesignParser

> Use this tool when you need to streamline your design process with evidence-backed rules and guidelines, solving problems such as inconsistent branding, poor user experience, and inefficient design decision-making. DesignParser provides a curated library of design rules and tools, including rule listing, search, and evaluation, with inputs such as design elements and outputs including suggested improvements. It is ideal for use in UI/UX design, visual design, and front-end development contexts.

Canonical page: https://skillsregistry.net/skills/designparser  
JSON: https://api.skillsregistry.net/v1/skills/designparser

## Description

DesignParser exposes a curated library of evidence-backed design rules as MCP tools, covering color, typography, spacing, shadows, UX laws, interaction, icons, visual design, and print. It provides five tools including rule listing, retrieval, fuzzy search, context-aware rule suggestion, and design evaluation. Rules include priority levels, sources, and related references. Available as the npm package designparser-mcp.

## Trust

- **Trust score (0–1):** 0.64
- **Verification tier:** scanned
- **Last scanned:** 2026-09-01

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** search
- **Updated:** 2026-09-01

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/designparser)
- **Repository:** <https://github.com/designparser/designparser-mcp>

## 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": "designparser"
    }
  }
}
```

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