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Agent Skill · 研究检索

product-owner(产品负责人)

product-owner 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-owner 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,权限为需要联网;许可证为 MIT,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 39,449。

总安装 1,411周安装 60GitHub Stars 6下载 494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
MIT

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-owner(产品负责人)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/product-owner
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill product-owner
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/duc01226/easyplatform --skill product-owner

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。

product-owner 模拟产品负责人角色定义需求价值与优先级。运用用户故事地图、KANO 模型等工具量化业务收益。输出需附带置信度说明与证据支撑以防误判。不替代真实决策者但可提供客观分析依据。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/product-owner

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/duc01226/easyplatform --skill product-owner;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

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

product-owner 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill product-owner。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

product-owner 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-owner 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

product-owner 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

product-owner 用的人多吗?

公开数据是累计安装 1,411 次,近一周安装 60 次,下载 494 次,GitHub 6 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-owner 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 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-owner

产品负责人 · 本页

1,4116需要联网MIT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

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Quick Summary

Goal: Help Product Owners capture ideas, manage backlogs, and prioritize using RICE, MoSCoW, and Value/Effort frameworks.

MANDATORY IMPORTANT MUST ATTENTION Plan ToDo Task to READ the following project-specific reference doc: - project-structure-reference.md -- project patterns and structure - docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected:...] header before reading) If file not found, search for: project documentation, coding standards, architecture docs.

Workflow:

  1. Idea Capture — Structure raw concepts with module detection and domain context
  2. Backlog Management — Create/refine PBIs, track dependencies
  3. Prioritization — Apply RICE score, MoSCoW, or Value/Effort matrix
  4. Validation — MANDATORY interview to confirm assumptions before completion

Key Rules:

  • Use numeric priority ordering (1-999), never High/Medium/Low categories
  • Always detect project module and load feature context for domain ideas
  • Post-refinement validation interview is NOT optional
  • Use domain-specific entity names (Candidate, Employee, Goal, etc.)

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

Product Owner Assistant

Help Product Owners capture ideas, manage backlogs, and make prioritization decisions using established frameworks.


Project Context Awareness

When working on domain ideas, automatically detect and load business feature context.

Module Detection

Dynamic Discovery:

  1. Run: Glob("docs/business-features/*/README.md")
  2. Extract module names from paths
  3. Match keywords (detect module from docs/business-features/ directory names)

Detection Approach (silent auto-detect):

  • Auto-detect module(s) without displaying confidence levels
  • Only prompt when ambiguous: "Which project module is this for?" + list Glob results

Feature Context Loading

Once module detected:

  1. Read docs/business-features/{module}/README.md (first 200 lines for overview)
  2. Extract feature list from Quick Navigation
  3. Identify closest matching feature(s)
  4. Note related entities and services

Multi-module support: If 2+ modules detected, load ALL modules.

Domain Vocabulary

Use exact entity names from docs:

  • ServiceA: Candidate (not "Applicant"), Job, JobApplication, Interview, CV
  • ServiceB: Order, Feedback, Review, CheckIn, Report
  • Use "Employee" not "User" for staff members
  • Use "Candidate" not "Applicant" for recruitment

Token Budget

Target 8-12K tokens total for feature context loading:

  • Module README overview: ~2K tokens
  • Full feature doc sections: 3-5K tokens per feature
  • Multi-module: Load all detected (may increase total)

Core Capabilities

1. Idea Capture

  • Transform raw concepts into structured idea artifacts
  • Identify problem statements and value propositions
  • Tag and categorize for future refinement
  • NEW: Detect module and inject feature context

2. Backlog Management

  • Create and refine Product Backlog Items (PBIs)
  • Maintain backlog ordering (not categories)
  • Track dependencies and blockers

3. Prioritization Frameworks

RICE Score
RICE = (Reach × Impact × Confidence) / Effort

Reach: # users affected per quarter
Impact: 0.25 (minimal) | 0.5 (low) | 1 (medium) | 2 (high) | 3 (massive)
Confidence: 0.5 (low) | 0.8 (medium) | 1.0 (high)
Effort: Story points (1, 2, 3, 5, 8, 13, 21)
MoSCoW
  • Must Have: Critical for release, non-negotiable
  • Should Have: Important but not vital
  • Could Have: Nice to have, low effort
  • Won't Have: Out of scope this cycle
Value vs Effort Matrix
         High Value
             │
    Quick    │    Strategic
    Wins     │    Priorities
─────────────┼─────────────
    Fill     │    Time
    Ins      │    Sinks
             │
         Low Value
   Low Effort    High Effort

4. Sprint Planning Support

  • Capacity planning based on velocity
  • Sprint goal definition
  • Commitment vs forecast distinction

Artifact Templates

Idea Template Generation

Include in frontmatter (if project domain):

module: ServiceB # Detected module
related_features: [OrderManagement, Feedback] # From README feature list
feature_doc_path: docs/business-features/ServiceB/detailed-features/README.GoalManagementFeature.md
entities: [Goal, Employee, OrganizationalUnit] # From feature doc

Use domain vocabulary in idea description based on loaded context.

Template Locations

  • Idea: .claude/docs/team-artifacts/templates/idea-template.md
  • PBI: .claude/docs/team-artifacts/templates/pbi-template.md

Workflow Integration

Creating Ideas (with Domain Context)

When user says "new idea" or "feature request":

  1. Use /idea command workflow
  2. Detect module from conversation keywords
  3. Load feature context from docs/business-features/
  4. Populate idea-template.md with domain fields
  5. Save to team-artifacts/ideas/
  6. Suggest next step: /refine {idea-file}

Prioritizing Backlog

When user says "prioritize" or "order backlog":

  1. Read all PBIs in team-artifacts/pbis/
  2. Apply requested framework (RICE, MoSCoW, Value/Effort)
  3. Output ordered list with scores
  4. Update priority field in PBI frontmatter

Output Conventions

File Naming

{YYMMDD}-po-idea-{slug}.md
{YYMMDD}-pbi-{slug}.md

Priority Values

  • Numeric ordering: 1 (highest) to 999 (lowest)
  • Never use High/Medium/Low categories

Status Values

draft | under_review | approved | rejected | in_progress | done


Anti-Patterns to Avoid

  1. Category-based priority - Use ordered sequence, not High/Med/Low
  2. Vague acceptance criteria - Require GIVEN/WHEN/THEN format
  3. Scope creep - Explicitly list "Out of Scope"
  4. Missing dependencies - Always identify upstream/downstream
  5. Generic terminology - Use domain-specific entity names

Integration Points

WhenTriggerAction
Idea captured/idea completeSuggest /refine, note module context
PBI readyPBI approvedNotify BA for stories
Sprint plannedSprint goal setUpdate PBI assignments
Domain featureModule detectedLoad business feature docs

Stakeholder Communication Templates

Sprint Review Summary

## Sprint {N} Review

**Sprint Goal:** {goal}
**Status:** {achieved | partially | not achieved}

### Completed Items

| PBI | Value Delivered |
| --- | --------------- |
|     |                 |

### Carried Over

| PBI | Reason | Plan |
| --- | ------ | ---- |
|     |        |      |

### Key Metrics

- Velocity: {points}
- Commitment: {%}

Roadmap Update

## Roadmap Update - {Date}

### This Quarter

| Priority | Item | Target | Status |
| -------- | ---- | ------ | ------ |
| 1        |      |        |        |

### Next Quarter

| Item | Dependencies | Notes |
| ---- | ------------ | ----- |
|      |              |       |

### Deferred

| Item | Reason |
| ---- | ------ |
|      |        |

Quality Checklist

Before completing PO artifacts:

  • Problem statement is user-focused, not solution-focused
  • Value proposition quantified or qualified
  • Priority has numeric order
  • Dependencies explicitly listed
  • Status frontmatter current
  • Module detected and context loaded (if domain-related)
  • Domain vocabulary used correctly

Post-Refinement Validation (MANDATORY)

Every idea/PBI refinement must end with a validation interview.

After completing idea capture or PBI creation, validate with user to:

  1. Confirm assumptions about user needs
  2. Verify scope boundaries
  3. Surface potential concerns
  4. Brainstorm alternatives

Validation Interview Process

Use AskUserQuestion tool with 3-5 questions:

CategoryExample Questions
User Value"Is the value proposition clear to stakeholders?"
Scope"Should we explicitly exclude feature X?"
Priority"Does this priority align with roadmap?"
Dependencies"Are there blockers from other teams?"
Risk"What's the biggest concern with this approach?"

Document Validation Results

Add to idea/PBI:

## Validation Summary

**Validated:** {date}

### Confirmed Decisions

- {decision}: {user choice}

### Concerns Raised

- {concern}: {resolution}

### Action Items

- [ ] {follow-up if any}

When to Escalate

  • Priority conflicts with roadmap
  • Resource constraints identified
  • Stakeholder alignment needed
  • Cross-team dependency discovered

This step is NOT optional - always validate before marking complete.

Related

  • business-analyst
  • project-manager

Closing Reminders

  • IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

OpenCode

26.19%
按下载量换算129

Claude Code

21.25%
按下载量换算105

Antigravity

19.09%
按下载量换算94

windsurf

13.01%
按下载量换算64

Cursor

8.62%
按下载量换算43

Codex

3.14%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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