TypingMindTypingMindThe best frontend for AI
Multica Test T1 Design logo

Multica Test T1 Design

Community
it235
multica-test-t1-design

T1 测试设计：AC↔设计追溯、用例模板与覆盖自检、Confluence 主副本、口令后 XMind/JIRA、Apifox 场景与 e2e 规划。整合 ac-design-trace + test-case-generator-squad。

Overview

Publisherit235
Repositorymultica-best-practices
Skill namemultica-test-t1-design
Stars
199
Forks
29
Bundled files
19
LicenseMIT
Links
Skill sourceRepository
  • 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.

  • 19 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Multica Test T1 Design 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/tester/multica-test-t1-design
  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/tester/multica-test-t1-design .claude/skills/multica-test-t1-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multica Test T1 Design 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 Test T1 Design 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 Test T1 Design 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.

Test Design（T1 测试设计 · 内容 + 落地）

定位

T1 唯一 skill：追溯 → 用例 → Confluence 全文 → 审核 →（👤 口令后）XMind/JIRA；并行 Apifox + 自动化规划。
不用于 T2/T3——T2 见 multica-test-t2-coverage；T3 见 -t3 + multica-test-orchestration。

层Skill职责
编排multica-test-orchestration跨阶段路由；自动化入仓见 references/automation-assets-lifecycle.md
T1本 skill内容 + Confluence + 口令后 XMind/JIRA
平台multica-platform-*读上游；Apifox 写场景
审核multica-review-test审 Confluence；只审不 import

三阶段交付：阶段 A 仅 Confluence（不生成 XMind）；👤 口令后阶段 C 才 XMind + JIRA。详见 references/generation-workflow.md。

Platform 协作

Platform skill本 skill 用途
multica-platform-jirafetch_all → get_issue.py；口令后 import_to_tracker.py（团队自备，见 references/import-contract.md）
multica-platform-confluence采集 fetch_page；发布 t1-cases.md（见 § Confluence 落地）
multica-platform-figmafetch_all → fetch_file.py
multica-platform-apifoxT1 并行写接口场景
团队知识库（可选）Step 0.5 术语/入口（用法二分；本仓库未随附，按所用平台接入）

凭据：JIRA_USERNAME / JIRA_PASSWORD 优先 → 见 platform skill + data-sources.md。

references/ 索引

文件用途
generation-workflow.md两阶段、口令、测试管理平台 命名/校验、步骤/优先级、去重/合并
executability-and-permissions.md权限识别顺序、双目标、模块命名、生成后自检
output-format.mdJSON 1:1、generated_summary、覆盖自查表、Output Delivery
multimodal-content.mdHTML/图片 Read 与融合理解
agent-instructions.md可复制 Agent 指令
design-trace.mdAC ↔ 设计追溯
test-case-template.md功能用例字段
coverage-dimensions.md维度选择、规模缩放、覆盖矩阵、XMind
coverage-checklist.md生成前自检清单
web-ui-checkpoints.mdFigma → UI 测试点
api-testing-guide.md接口场景模式
data-sources.md采集编排与凭据

T1 流程

Step 0 — 读 MULTICA.md（自动化路径）

Issue 仓库矩阵 → 每个 repo Read 根目录 MULTICA.md §2（分仓各一份；同仓一份须完整）。缺则 BLOCKED。

Step 0.5 — 知识库（Step 0.5）

团队知识库问答脚本（可选接入）→ --health + 问答。用法二分：操作桶进步骤，规则桶不当 AC。见 generation-workflow.md。

Step 1 — 设计追溯

design-trace.md → 追溯表写入覆盖报告。

Step 2 — 采集

bash
python scripts/fetch_all.py --jira-url "http://jira.../browse/PROJ-123" -o ./data

多模态：multimodal-content.md。

Step 3–4 — 用例 + 自检

按 test-case-template.md + generation-workflow.md + output-format.md → 本地 JSON（工作文件）；coverage-checklist.md 自检。不写 XMind。

Step 5 — 阶段 A：Confluence + Apifox 并行

  • 将 完整用例正文 写入 docs/test/<ISSUE-KEY>/t1-cases.md（模板见 platform-confluence test-t1-template.md）
  • Confluence 落地（见下 §）→ 回传链接
  • API 契约就绪 → multica-platform-apifox 按契约补场景（AI 分支；写 manifest 规划节）
  • → multica-review-test（审 Confluence）
  • 交付语：状态：待人工审核（Confluence 已更新，未 XMind/未导入 JIRA）

Step 6 — 阶段 C：XMind + JIRA（👤 明确口令后）

  1. generate_xmind.py ← 最新 JSON（与 Confluence 一致）
  2. import_to_tracker.py（团队自备，接口见 references/import-contract.md）
  3. republish Confluence 状态「已导入 JIRA」+ 用例集链接

Confluence 落地（T1 · 主副本）

父页面：JIRA Issue Hub（PRD 需求页）子页面。

本地草稿：docs/test/<ISSUE-KEY>/t1-cases.md
基线：multica-platform-confluence/scripts/templates/test-t1-template.md

须含 每条 CASE 步骤/预期正文、Apifox 节、UI e2e 规划（路径写 MULTICA.md §2，非硬编码）。T1/T2 不生成 XMind。

发布：

bash
python multica-platform-confluence/scripts/publish_design.py \
  <ISSUE-KEY> docs/test/<ISSUE-KEY>/t1-cases.md \
  --append-jira --json

JIRA 块：h3. T1 测试用例 (Test Cases T1)。

Apifox（T1 并行）

契约发布后：读 API 契约 → multica-platform-apifox 补场景（AI 分支）→ Confluence 记录 branch/scenario → manifest 路径见 MULTICA.md §2。

Files

text
multica-test-t1-design/
├── SKILL.md
├── config.local.env.example
├── references/
└── scripts/

为什么有效

T1 内容与脚本合一；generation-workflow + output-format 保留原版 generator 硬规则；platform 统一采集 REST。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Multica Test T1 Design AI skill do?

T1 测试设计：AC↔设计追溯、用例模板与覆盖自检、Confluence 主副本、口令后 XMind/JIRA、Apifox 场景与 e2e 规划。整合 ac-design-trace + test-case-generator-squad。

Why use Multica Test T1 Design on TypingMind?

Because you install it once and use it with any model. Multica Test T1 Design 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 Test T1 Design 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/tester/multica-test-t1-design. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Multica Test T1 Design?

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 Test T1 Design?

As many as you like. As long as a model supports skills, you can use Multica Test T1 Design with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Multica Test T1 Design 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.

Related AI Skills

View all
openclaw logo

Canvas

openclaw
OrganizationPopular

Present hosted widget documents on a connected macOS panel and control panel visibility or navigation.

82.2K
391K
Instructions
View
openclaw logo

Diagram Maker

openclaw
OrganizationPopular

Create SVG/HTML or Excalidraw diagrams for concepts, architecture, flows, and whiteboards.

82.2K
391K
2 files
View
mattpocock logo

Grill With Docs

mattpocock
CommunityPopular

A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.

23K
273.1K
1 files
View
mattpocock logo

Grill Me

mattpocock
CommunityPopular

A relentless interview to sharpen a plan or design.

23K
273.1K
1 files
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇