Multica Artifact Frontend

Community

it235

multica-artifact-frontend

前端产物薄编排：实现说明文档规范，落地调 multica-platform-confluence + multica-platform-jira。用于 @FrontendDev 发布交互/页面对照说明。

Overview

Publisher	it235
Repository	`multica-best-practices`
Skill name	`multica-artifact-frontend`
Stars	199
Forks	29
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 Artifact Frontend AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/it235/multica-best-practices/tree/main/templates/zh_CN/skills/frontend/multica-artifact-frontend
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/it235/multica-best-practices/tree/main/templates/zh_CN/skills/frontend/multica-artifact-frontend

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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/frontend/multica-artifact-frontend .claude/skills/multica-artifact-frontend

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multica Artifact Frontend 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 Artifact Frontend 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 Artifact Frontend 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.

Artifact · Frontend（薄编排）

Purpose

只规定前端实现说明写什么、发布前怎么自检；Confluence 发布、JIRA 回写由 platform skill 封装。代码在真实仓库，本文档供评审 / 测试 / Leader 对照。

本 skill 不含脚本；编码与体验见 multica-frontend-impl。

Platform 协作

Platform skill	本 skill 用途
`multica-platform-jira`	读 Issue / 回写 impl-spec 链接
`multica-platform-confluence`	发布 `impl-spec.md` 到 Issue Hub 子页
`multica-platform-figma`	读设计链接（上游由 Designer / Issue 提供）

凭据与 CLI 细节只查 platform skill。

@FrontendDev 标准流程

text
1. multica-frontend-impl       — 读上游（PRD/架构/UI/API）
2. 写 docs/frontend/<ISSUE-KEY>/impl-spec.md（开工前或实现中更新）
3. 自检（见下表）
4. multica-platform-confluence — publish_design.py --append-jira
5. 实现页面/组件 + 测试
6. 回传 Confluence 链接 + 代码证据给 Leader

父页面（Issue Hub）

JIRA 描述中 Confluence 需求页 为父页面；前端实现说明发布为其子页面（与架构设计、API 契约并列）。

实现说明规范（发布前自检）

本地草稿：docs/frontend/<ISSUE-KEY>/impl-spec.md
基线：multica-platform-confluence/scripts/templates/frontend-impl-template.md

章节	必填	内容要求
文档头部	是	创建者、时间、版本、状态、JIRA、PRD、架构、UI、API 链接
页面与路由	是	页面 · 路由 · 入口 · AC-
交互与状态	是	操作/反馈；空态/加载/异常/无权限
组件映射	是	UI 区域 · 组件 · 复用/新建
API 对接	涉及时	API-ID · 调用时机 · 错误 UX
表单与校验	涉及时	规则 · 提示文案 · BR-
体验与无障碍	按需	响应式、键盘、性能感知
Mock 策略	后端未就绪时	Mock 位置与切换条件
验证计划	是	组件/手动/E2E · AC-
修订记录	是	版本递增

自检 FAIL → 先补文档，不调 platform。

落地（platform skill）

bash
pip install -r multica-platform-confluence/scripts/requirements.txt
python multica-platform-confluence/scripts/publish_design.py \
  <ISSUE-KEY> docs/frontend/<ISSUE-KEY>/impl-spec.md \
  --append-jira --json

JIRA 追加块：h3. 前端实现说明 (Frontend Implementation)。

用法（角色侧）

text
按 multica-artifact-frontend 规范写 impl-spec.md，
自检后 platform 发布到 Confluence 并回传链接。

为什么有效

把「交互与状态」从代码里抽成可评审文档，挂需求树下；与后端契约、架构设计同 Hub，下游不迷路。

Frequently asked questions

What does the Multica Artifact Frontend AI skill do?

前端产物薄编排：实现说明文档规范，落地调 multica-platform-confluence + multica-platform-jira。用于 @FrontendDev 发布交互/页面对照说明。

Why use Multica Artifact Frontend on TypingMind?

Because you install it once and use it with any model. Multica Artifact Frontend 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 Artifact Frontend 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/frontend/multica-artifact-frontend. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Multica Artifact Frontend?

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 Artifact Frontend?

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

Is the Multica Artifact Frontend 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Artifact · Frontend（薄编排）

Purpose

Platform 协作

@FrontendDev 标准流程

父页面（Issue Hub）

实现说明规范（发布前自检）

落地（platform skill）

用法（角色侧）

为什么有效

Frequently asked questions

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