Token导航 LogoToken导航

Agent Skill · 研究检索

product-sense-interview-answer(product sense interview answer 搜索)

product-sense-interview-answer 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

product-sense-interview-answer 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 18,247。

总安装 6,190周安装 267GitHub Stars 3,919下载 2,072核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:product-sense-interview-answer(product sense interview answer 搜索)
来源仓库:https://github.com/deanpeters/product-manager-skills
仓库路径:skills/product-sense-interview-answer
安装命令:
npx skills add https://github.com/deanpeters/product-manager-skills --skill product-sense-interview-answer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/deanpeters/product-manager-skills --skill product-sense-interview-answer

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。通过 npx skills add 命令从指定仓库安装,需结合原始 README 核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

product-sense-interview-answer 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/product-sense-interview-answer

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/deanpeters/product-manager-skills --skill prod…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

product-sense-interview-answer 怎么安装?

在终端执行 npx skills add https://github.com/deanpeters/product-manager-skills --skill product-sense-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

product-sense-interview-answer 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

product-sense-interview-answer 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

product-sense-interview-answer 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

product-sense-interview-answer 用的人多吗?

公开数据是累计安装 6,190 次,近一周安装 267 次,下载 2,072 次,GitHub 3,919 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

product-sense-interview-answer 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 来源仓库有 3,919 星,维护活跃度相对可查。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
product-sense-interview-answer

product sense interview answer 搜索 · 本页

6,1903,919只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Purpose

Help PM candidates and interview coaches structure product-sense answers that sound strong out loud, not just on paper. Use this when practicing prompts like "How would you improve X?", "Design a product for Y", or "What would you build next for Z?"

This is not a memorize-and-recite script. It is a reasoning scaffold that prevents solution-jumping, forces real prioritization, and leaves the interviewer with a clean story they can follow.

Key Concepts

What Product Sense Interviews Actually Test

Strong product-sense answers do more than generate ideas. Interviewers are usually testing whether you can:

  • Clarify ambiguous prompts without getting stuck
  • Tie user value to market or business logic
  • Segment thoughtfully instead of talking about "everyone"
  • Prioritize one pain point instead of describing ten equally
  • Make tradeoffs explicit when choosing an MVP
  • Communicate clearly under time pressure

The Six-Part Answer Spine

  1. Clarify - Reduce ambiguity, define scope, and state assumptions.
  2. Rationale - Explain why the problem matters now for the market and, if relevant, the company.
  3. Product Goal - Define the user outcome you want to create before talking about features.
  4. Segmentation - Choose who to serve first and show why that target wins.
  5. Pain Points - Map the journey, name the main frictions, and pick the one worth solving first.
  6. Solution - Generate distinct options, compare them, and commit to one MVP with clear exclusions.

The order matters. If you skip from prompt to feature ideas, your answer sounds clever but ungrounded. If you establish the user, goal, and pain first, your solution feels earned.

Why This Works

  • Prevents feature dumping: You do not start with ideas before you know whose problem you are solving.
  • Balances user and business thinking: The answer includes demand, company fit, and strategic tradeoffs rather than pure UX talk.
  • Creates a speakable narrative: Each section becomes a short checkpoint the interviewer can follow.
  • Forces prioritization: Reach, impact, fit, frequency, severity, and effort all surface tradeoffs instead of hand-wavy optimism.

Anti-Patterns (What This Is NOT)

  • Not a feature brainstorm: Listing ideas without choosing a target user or problem is not product sense.
  • Not a TAM presentation: You do not need made-up market numbers to sound strategic.
  • Not a memorized monologue: Rigid scripts break as soon as the interviewer redirects or narrows scope.
  • Not a business-case-only answer: Product sense still requires empathy, behavior, and user context.

When to Use This

  • Product design questions
  • Product improvement questions
  • "What would you build next?" prompts
  • Mock interviews where you want a repeatable spoken structure

When NOT to Use This

  • Behavioral interviews that need STAR stories
  • Execution and analytics cases that revolve around metrics diagnosis
  • Go-to-market or pricing interviews where distribution or monetization is the main problem

Application

Use template.md as the working structure.

Delivery Rules

  • State your structure early so the interviewer knows where you are going.
  • Ask only 1-2 clarifying questions. More than that feels like stalling.
  • Keep lists MECE where possible: segments should be distinct, pain points should not overlap, and solutions should not be three versions of the same thing.
  • Speak in short sentences. Interview answers should sound conversational, not like a memo read aloud.
  • If the prompt does not name a company, use a startup assumption and skip fake company-mission talk.

Step 1: Clarify the Prompt

Start by surfacing the two ambiguities that change the answer most. Good clarifiers usually narrow:

  • Product or surface area
  • User group
  • Time horizon
  • Business model or operating constraints

If the interviewer does not answer, state your assumptions and move on. The goal is to unblock the rest of the answer, not to turn the interview into requirements gathering.

Quality bar: Ask questions that materially change the solution. "Are we talking mobile or desktop?" matters less than "Are we optimizing for viewers, creators, or advertisers?"

Step 2: Build the Rationale Before the Feature

Explain why the space matters now.

For the market view, cover:

  • Why the market is big or strategically important
  • Why the problem matters to real people
  • Why now is a good moment to act

If a company is named, then add:

  • Mission fit
  • Business objective
  • Competitive landscape
  • Market gap
  • Unique strength

End this section with a one-line thesis. That thesis should make the rest of the answer feel inevitable.

Quality bar: Use qualitative signals unless you know the numbers cold. Fake precision is worse than grounded judgment.

Step 3: Define the Product Goal

Write one sentence in this format:

Help [user] [achieve outcome], so that [broader impact].

Then describe what success looks like for the user in observable terms.

Good: "Help beginner YouTube learners find content they are glad they watched, so that the platform becomes an intentional learning destination."

Bad: "Build a personalized AI learning path feature." That is a solution disguised as a goal.

Step 4: Segment the Market and Pick a Target

Do not jump straight to persona. First identify the ecosystem players, then choose the player you want to serve. After that, choose two segmentation dimensions that actually change needs.

Good segmentation dimensions usually change:

  • Goal or job to be done
  • Stakes or consequence level
  • Expertise level
  • Workflow constraints
  • Frequency of the problem

Weak dimensions are often demographic cuts that do not change the product meaningfully.

After choosing your target segment:

  • Give a brief reach / impact / strategic-fit rationale
  • Write a two-sentence persona
  • Keep the persona free of pain points; pain comes next

Step 5: Map Pain Points and Prioritize One

Break the user journey into 4-6 stages. Then list the frictions across that journey.

Prioritize the top pain point using:

  • Frequency - how often the user hits it
  • Severity - how badly it blocks the job, how underserved it is, and the emotional cost

This is the fulcrum of the entire answer. If the pain point is vague or weak, the solution section becomes generic.

Quality bar: Pain points should describe user friction, not missing features. "No structured progression after each video" is a pain. "No AI learning path" is already a solution.

Step 6: Generate Options, Choose an MVP, and Close

List three distinct solutions. They should solve the same pain in different ways, not represent three feature line-items inside one idea.

Evaluate each option on:

  • User impact
  • Effort

Then choose one MVP and specify:

  • Core features
  • 1-2 explicit v1 exclusions
  • Top risks and mitigations

Close with a one-sentence recap that names:

  • Target segment
  • Top pain point
  • First bet

That final sentence is what the interviewer should remember.

Examples

Good Example: Improve YouTube for Beginner Learners

See examples/improve-youtube.md for a full worked example.

What makes it strong:

  • It chooses one player first: viewers, not "everyone in the ecosystem"
  • It segments by learning intent and expertise level, which both change needs materially
  • It picks one pain point: no structured progression across videos
  • It compares multiple solutions before choosing Learning Paths as the MVP

Good Example: Design a Fire Alarm for the Deaf

A strong answer to this prompt would explicitly state a startup assumption if no company is named, prioritize people who live alone, and choose the wake-up problem before discussing dispatch or smart-home integrations.

What makes this example useful:

  • The target segment is clear and high-stakes
  • Severity matters more than broad reach
  • Hardware, software, and ecosystem constraints are part of the reasoning

Anti-Pattern Example

"I would improve YouTube by adding AI summaries, better recommendations, creator analytics, and a study mode."

Why this fails:

  • No target user
  • No prioritized pain point
  • No business or market logic
  • Four ideas that were never compared against each other

This kind of answer can sound energetic in the moment, but it signals weak PM judgment.

Common Pitfalls

  • Solution-first thinking: You start pitching features before naming the user or problem. Fix it by forcing yourself to write the product goal and top pain point before brainstorming solutions.
  • Segmentation theater: You list many segments, then pick one with no tradeoff logic. Fix it by explicitly comparing reach, impact, and strategic fit.
  • Goal-as-feature: Your "goal" describes the thing you want to build. Fix it by rewriting it as a user outcome.
  • Pain points that are really solutions: "Users need a dashboard" is not a pain point. Rewrite in user-language first.
  • Three fake options: Your three solutions are really one solution with minor variations. Fix it by varying the product mechanism, not just the packaging.
  • Weak close: You end after listing features. Fix it by restating the target segment, the pain, and the first bet in one sentence.
  • Over-answering every branch: You try to prove breadth instead of making choices. Product-sense interviews reward focus more than exhaustiveness.

References

平台分布

Codex

33.21%
按下载量换算688

Claude

29.47%
按下载量换算611

Cursor

19.8%
按下载量换算410

Gemini CLI

9.84%
按下载量换算204

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills