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Multica Pm Requirement Spec

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it235
multica-pm-requirement-spec

产品经理需求规范：把 Issue/诉求结构化为带编号 PRD（G-/FR-/BR-/AC-/KPI-/OP-/RISK-）。含知识库背景检索；结构就绪后交 multica-pm-artifact-publish 落地。

Overview

Publisherit235
Repositorymultica-best-practices
Skill namemultica-pm-requirement-spec
Stars
199
Forks
29
Bundled files
1
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.

  • 1 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 Pm Requirement Spec 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/product-manager/multica-pm-requirement-spec
  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/product-manager/multica-pm-requirement-spec .claude/skills/multica-pm-requirement-spec
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multica Pm Requirement Spec 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 Pm Requirement Spec 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 Pm Requirement Spec 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.

PM Requirement Spec（产品经理需求规范 · 内容）

Purpose

把 Issue、会议结论、零散想法变成清晰、可评审、可拆任务的 PRD 内容（只管「写什么」，不管「落到哪个平台」）。

与 multica-pm-artifact-publish 分工：本 skill = 需求规范与编号；publish = Confluence / JIRA 创建与更新。换平台只改 publish，不动本 skill。

Platform 协作

Platform skill本 skill 用途
团队知识库（可选）Step 0.5 查术语、历史需求背景（参考，不当新 AC）
multica-platform-jira / multica-platform-confluence不直接调用；读写由 multica-pm-artifact-publish 编排

智能体指令见 references/agent-instructions.md。

两阶段（规范 ≠ 提交）

阶段动作停止点
A 结构化采集 + KB → 编号 PRD 草稿交付 Markdown/HTML 草稿 + 修订记录
B 提交用户/Leader 确认范围后 → multica-pm-artifact-publish回传 Confluence + JIRA 链接

Review 后修订：回到阶段 A 改内容 → 再调 publish 更新（非重复创建）。详见 publish skill Workflow B。

Step 0.5 — 知识库（用法二分）

调用 团队知识库（可选） → kb_ask.py（禁止 SSH/curl）。

信息类型能否写进 PRD写哪里
术语、模块边界、历史背景参考背景/修订记录/OP- 引用
菜单路径、权限名、字段别名（当前需求相关）应当使用FR-/BR-/AC- 可执行描述
历史规则、他系统口径、当前需求未写的字段禁止当新 FR/AC仅背景；冲突以当前 Issue 为准

138 不可用：标注「知识库不可用」，不阻断结构化；禁止臆造业务规则。超时停轮见 platform KB SKILL。

Process

  1. 识别业务目标（G- + KPI-）
  2. 用户角色 / 权限
  3. 范围（含 / 不含）与非目标
  4. 约束（兼容性 / 性能 / 安全 / 时间）
  5. 验收标准（AC-，可测试）
  6. 歧义 → OP- 待确认清单
  7. 依赖与风险（RISK-）

Requirement Structure

章节基线见 multica-platform-confluence 的 scripts/templates/prd-template.md：

章节编号
一句话定义、背景—
目标与成功标准G- + KPI-
用户故事U-
功能需求FR-
业务规则BR-
验收标准AC-
待确认项OP-
风险项RISK-

正式 PRD 至少包含：一句话定义、背景、G-/KPI-、用户与权限、范围、FR-/BR-/AC-、字段口径、空态/异常态/无权限态、RISK-/OP-、修订记录。

Output

  • 目标（G-）、范围、非目标
  • 验收标准（AC-）、约束、依赖
  • 待确认项（OP-）、风险（RISK-）
  • 修订记录：版本号、日期、变更摘要（Review 修订后必递增）

Rule

歧义会实质影响实现 → BLOCKED → 说明缺什么、谁提供，只问 1 个最关键问题。

Review 后修订（与 multica-review-product）

Review 结论PM 动作
FAIL按修改清单改 PRD 编号条目 → 更新修订记录 → multica-pm-artifact-publish Workflow B 更新 → 请 ProductReviewer 复审
PASS交 Leader multica-verification；OP- 未关闭项仍不得进开发

ProductReviewer 只评不改；PM 在用户/Leader 授权「按 review 修订」后执行修订。

Handoff

text
1. multica-pm-requirement-spec   — 结构化 PRD（本 skill）
2. multica-pm-artifact-publish — Confluence + JIRA 创建/更新 + 可选钉钉

为什么有效

需求歧义在下游放大。编号 + OP- 清单 + KB 背景（不扩 scope）让 PRD 可评审、可测；内容与平台解耦，Review 后可二次更新而不重复建 Story。

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 Pm Requirement Spec AI skill do?

产品经理需求规范：把 Issue/诉求结构化为带编号 PRD（G-/FR-/BR-/AC-/KPI-/OP-/RISK-）。含知识库背景检索；结构就绪后交 multica-pm-artifact-publish 落地。

Why use Multica Pm Requirement Spec on TypingMind?

Because you install it once and use it with any model. Multica Pm Requirement Spec 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 Pm Requirement Spec 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/product-manager/multica-pm-requirement-spec. 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 Pm Requirement Spec?

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 Pm Requirement Spec?

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

Is the Multica Pm Requirement Spec 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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