Pm/Requirement Penetration

Community

echoVic

pm/requirement-penetration

深度挖掘用户需求的方法论，通过5W2H追问和需求分层模型，识别显性、隐性、潜在和惊喜需求

Overview

Publisher	echoVic
Repository	`boss-skill`
Skill name	`pm/requirement-penetration`
Stars	562
Forks	51
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 echoVic on GitHub. Read the source before you install it.

Installation

Install the Pm/Requirement Penetration 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/echoVic/boss-skill/tree/main/skill/skills/pm/requirement-penetration
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.

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/echoVic/boss-skill.git /tmp/boss-skill
mkdir -p .claude/skills
cp -r /tmp/boss-skill/skill/skills/pm/requirement-penetration .claude/skills/echovic-pm-requirement-penetration

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

Use it in TypingMind

Enable Pm/Requirement Penetration 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 Pm/Requirement Penetration 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 Pm/Requirement Penetration 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.

需求穿透方法论

适用场景

当用户提出需求时，不要直接接受表面描述。使用本方法论深度挖掘用户真正想要什么，识别用户没说出口的需求，甚至发现用户自己都没意识到的需求。

核心方法

需求分层模型

用户需求分为四个层次，从下到上价值递增：


        ┌─────────────────┐
        │   惊喜需求      │ ← 超出预期，带来 "Wow"
        │   (Delighters)  │
        ├─────────────────┤
        │   潜在需求      │ ← 用户尚未意识到
        │   (Latent)      │
        ├─────────────────┤
        │   隐性需求      │ ← 用户想到但未说
        │   (Implicit)    │
        ├─────────────────┤
        │   显性需求      │ ← 用户明确表达
        │   (Explicit)    │
        └─────────────────┘

四层需求定义：

显性需求：用户明确表达的需求
- 直接从用户原话中提取
- 这是需求分析的起点，不是终点
隐性需求：用户想到但未表达的需求
- 用户认为"理所当然"而没说的
- 用户不好意思说的
- 用户以为你会知道的
潜在需求：用户尚未意识到但会需要的需求
- 基于场景推演发现的需求
- 基于竞品分析发现的需求
- 基于行业趋势预判的需求
惊喜需求：超出用户预期、能带来 "Wow" 体验的需求
- 创新性的功能或体验
- 让用户感到"这个太棒了！"
- 这是产品差异化的关键

5W2H 深度追问

对每个需求，系统性地追问以下7个维度：

维度	问题	目的
What	用户说的是什么？背后真正想要的是什么？	识别真实需求
Why	为什么需要这个？解决什么问题？	理解动机
Who	谁会用？在什么场景下用？	明确用户
When	什么时候用？频率如何？	理解场景
Where	在哪里用？环境如何？	理解上下文
How	现在怎么解决的？有什么痛点？	发现机会
How much	愿意付出多少？（时间/金钱/学习成本）	评估价值

追问技巧：

至少追问 "为什么" 5次，直到触及根本动机
不要满足于第一个答案
关注用户的情绪和语气，往往隐藏着真实需求

需求优先级矩阵

基于价值和成本，将需求分为4个优先级：


        高价值
           │
    ┌──────┼──────┐
    │ 必做 │ 优先 │
    │ P0   │ P1   │
低成本 ────┼──── 高成本
    │ 可做 │ 谨慎 │
    │ P2   │ P3   │
    └──────┼──────┘
           │
        低价值

P0（必做）：高价值 + 低成本 = 必须做
P1（优先）：高价值 + 高成本 = 优先做
P2（可做）：低价值 + 低成本 = 可以做
P3（谨慎）：低价值 + 高成本 = 暂不做

输出要求

完成需求穿透后，应输出以下内容（通常作为PRD的第2章）：

2. 需求穿透分析

2.1 用户原始需求

[用户的原始表述，保持原话]

2.2 需求穿透

显性需求（用户明确表达的）

需求	用户原话	解读
[需求 1]	"[原话]"	[你的解读]
[需求 2]	"[原话]"	[你的解读]

隐性需求（用户想到但未表达的）

需求	推断依据	为什么重要
[需求 1]	[依据]	[重要性]
[需求 2]	[依据]	[重要性]

潜在需求（用户尚未意识到的）

需求	洞察来源	预期价值
[需求 1]	[来源]	[价值]
[需求 2]	[来源]	[价值]

惊喜需求（超出预期的创新点）

需求	创新点	预期反应
[需求 1]	[创新点]	"Wow, 这个太棒了！"
[需求 2]	[创新点]	[预期反应]

2.3 需求优先级矩阵

优先级	需求	价值	成本	决策
P0	[需求]	高	低	必须做
P1	[需求]	高	高	优先做
P2	[需求]	低	低	可以做
P3	[需求]	低	高	暂不做

关键原则

不要急于给答案：先理解问题，再提供方案
挑战假设：用户说的不一定是对的，要验证
关注痛点：真正的需求来自真实的痛苦
追求惊喜：好产品不只是满足需求，更要超越预期

Frequently asked questions

What does the Pm/Requirement Penetration AI skill do?

深度挖掘用户需求的方法论，通过5W2H追问和需求分层模型，识别显性、隐性、潜在和惊喜需求

Why use Pm/Requirement Penetration on TypingMind?

Because you install it once and use it with any model. Pm/Requirement Penetration 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 Pm/Requirement Penetration in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/echoVic/boss-skill/tree/main/skill/skills/pm/requirement-penetration. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Pm/Requirement Penetration?

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 Pm/Requirement Penetration?

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

Is the Pm/Requirement Penetration AI skill free?

Yes. It is published on GitHub by echoVic 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.

View all

Wasm Gallery

ruvnet

CommunityPopular

Browse, publish, and install WASM agents from the community gallery

Browser Extract

Extract structured data via stored browser-templates or one-shot DOM queries, with mandatory AIDefence PII + prompt-injection gates before content reaches the model

Browser Record

Open a named, traced browser session into an RVF cognitive container with a ruvector trajectory recording every action

Init Project

Initialize a new Ruflo project with MCP tools, hooks, and agent configuration. Use when setting up Ruflo in a fresh repo, or when the user says "init ruflo", "set up ruflo", or asks how to bootstrap…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

需求穿透方法论

适用场景

核心方法

需求分层模型

5W2H 深度追问

需求优先级矩阵

输出要求

2. 需求穿透分析

2.1 用户原始需求

2.2 需求穿透

2.3 需求优先级矩阵

关键原则

Frequently asked questions

Related AI Skills

Set up your own AI workspace now