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Multica Review Designer

Community
it235
multica-review-designer

UI 设计专属评审框架。由 DesignReviewer 调用,对 Designer 产出的 UI/交互设计做专业分析(交互合理性/可访问性/设计系统一致/边界态),输出 PASS/FAIL 与修改清单,汇报 Leader。

Overview

Publisherit235
Repositorymultica-best-practices
Skill namemultica-review-designer
Stars
199
Forks
29
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by it235 on GitHub. Read the source before you install it.

Installation

Install the Multica Review Designer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/it235/multica-best-practices/tree/main/templates/zh_CN/skills/reviewer/multica-review-designer
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/it235/multica-best-practices.git /tmp/multica-best-practices
mkdir -p .claude/skills
cp -r /tmp/multica-best-practices/templates/zh_CN/skills/reviewer/multica-review-designer .claude/skills/multica-review-designer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multica Review Designer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Multica Review Designer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Multica Review Designer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

UI 设计专业评审(DesignReviewer)

本 skill 提供对 UI / 交互设计产物的结构化专业评审框架。调用方为 DesignReviewer,评审对象为 Designer 经 团队设计实现 skill(可选,本仓库未随附) 回传的 Figma/设计平台链接。

什么时候用

  • DesignReviewer 收到 Leader 派发的「评审 UI 设计」任务时。
  • 设计修改后进入复审轮次时(对照上一轮修改清单逐条核对)。

评审维度(逐项给结论)

  1. 交互合理性:操作流程是否顺畅,是否符合用户心智模型,有无冗余步骤。
  2. 可访问性:对比度、焦点管理、无障碍标注是否到位。
  3. 设计系统一致性:组件、字号、间距、状态是否对齐设计系统/验收约定。
  4. 边界态:空态、加载态、错误态、超长文本是否被覆盖。
  5. 技术可行性:是否存在明显不可实现或高成本的交互(标记并交 Leader 收敛)。

输出格式

text
【UI 设计评审】<设计链接>
结论:PASS / FAIL
阻断项(FAIL 时必填,每项含 理由 / 涉及点 / 修改方向):
- ...
建议项(非阻断):
- ...
与上一轮修改清单核对(复审时):已解决 X 项 / 未解决 Y 项
轮次:第 N / 3 轮

结论与修改清单汇报给 Leader,不自行改设计、不自行通知 Designer。

边界

  • 只评 UI 设计,不评架构、需求、代码、测试用例。
  • 不替代 Leader 的通用门禁(multica-verification skill)。
  • 第 3 轮仍 FAIL → 标注「升级人类」,交 Leader 处理,停止循环。

Frequently asked questions

What does the Multica Review Designer AI skill do?

UI 设计专属评审框架。由 DesignReviewer 调用,对 Designer 产出的 UI/交互设计做专业分析(交互合理性/可访问性/设计系统一致/边界态),输出 PASS/FAIL 与修改清单,汇报 Leader。

Why use Multica Review Designer on TypingMind?

Because you install it once and use it with any model. Multica Review Designer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Multica Review Designer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/it235/multica-best-practices/tree/main/templates/zh_CN/skills/reviewer/multica-review-designer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Multica Review Designer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Multica Review Designer?

As many as you like. As long as a model supports skills, you can use Multica Review Designer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Multica Review Designer AI skill free?

Yes. It is published on GitHub by it235 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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