Product Manager Toolkit Agent Skill

Product Manager Toolkit

Essential tools and frameworks for modern product management, from discovery to delivery.

Quick Start

For Feature Prioritization

python scripts/rice_prioritizer.py sample  # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15

For Interview Analysis

python scripts/customer_interview_analyzer.py interview_transcript.txt

For PRD Creation

• Choose template from references/prd_templates.md
• Fill in sections based on discovery work
• Review with stakeholders
• Version control in your PM tool

Core Workflows

Feature Prioritization Process

• Gather Feature Requests
• Customer feedback
• Sales requests
• Technical debt
• Strategic initiatives

• Score with RICE

   # Create CSV with: name,reach,impact,confidence,effort
   python scripts/rice_prioritizer.py features.csv

• Reach: Users affected per quarter
• Impact: massive/high/medium/low/minimal
• Confidence: high/medium/low
• Effort: xl/l/m/s/xs (person-months)

• Analyze Portfolio
• Review quick wins vs big bets
• Check effort distribution
• Validate against strategy

• Generate Roadmap
• Quarterly capacity planning
• Dependency mapping
• Stakeholder alignment

Customer Discovery Process

• Conduct Interviews
• Use semi-structured format
• Focus on problems, not solutions
• Record with permission

• Analyze Insights

   python scripts/customer_interview_analyzer.py transcript.txt

Extracts:

• Pain points with severity
• Feature requests with priority
• Jobs to be done
• Sentiment analysis
• Key themes and quotes

• Synthesize Findings
• Group similar pain points
• Identify patterns across interviews
• Map to opportunity areas

• Validate Solutions
• Create solution hypotheses
• Test with prototypes
• Measure actual vs expected behavior

PRD Development Process

• Choose Template
• Standard PRD: Complex features (6-8 weeks)
• One-Page PRD: Simple features (2-4 weeks)
• Feature Brief: Exploration phase (1 week)
• Agile Epic: Sprint-based delivery

• Structure Content
• Problem → Solution → Success Metrics
• Always include out-of-scope
• Clear acceptance criteria

• Collaborate
• Engineering for feasibility
• Design for experience
• Sales for market validation
• Support for operational impact

Key Scripts

rice_prioritizer.py

Advanced RICE framework implementation with portfolio analysis.

Features:

• RICE score calculation
• Portfolio balance analysis (quick wins vs big bets)
• Quarterly roadmap generation
• Team capacity planning
• Multiple output formats (text/json/csv)

Usage Examples:

# Basic prioritization
python scripts/rice_prioritizer.py features.csv

# With custom team capacity (person-months per quarter)
python scripts/rice_prioritizer.py features.csv --capacity 20

# Output as JSON for integration
python scripts/rice_prioritizer.py features.csv --output json

customer_interview_analyzer.py

NLP-based interview analysis for extracting actionable insights.

Capabilities:

• Pain point extraction with severity assessment
• Feature request identification and classification
• Jobs-to-be-done pattern recognition
• Sentiment analysis
• Theme extraction
• Competitor mentions
• Key quotes identification

Usage Examples:

# Analyze single interview
python scripts/customer_interview_analyzer.py interview.txt

# Output as JSON for aggregation
python scripts/customer_interview_analyzer.py interview.txt json

Reference Documents

prd_templates.md

Multiple PRD formats for different contexts:

• Standard PRD Template
• Comprehensive 11-section format
• Best for major features
• Includes technical specs

• One-Page PRD
• Concise format for quick alignment
• Focus on problem/solution/metrics
• Good for smaller features

• Agile Epic Template
• Sprint-based delivery
• User story mapping
• Acceptance criteria focus

• Feature Brief
• Lightweight exploration
• Hypothesis-driven
• Pre-PRD phase

Prioritization Frameworks

RICE Framework

Score = (Reach × Impact × Confidence) / Effort

Reach: # of users/quarter
Impact: 
  - Massive = 3x
  - High = 2x
  - Medium = 1x
  - Low = 0.5x
  - Minimal = 0.25x
Confidence:
  - High = 100%
  - Medium = 80%
  - Low = 50%
Effort: Person-months

Value vs Effort Matrix

         Low Effort    High Effort
         
High     QUICK WINS    BIG BETS
Value    [Prioritize]   [Strategic]
         
Low      FILL-INS      TIME SINKS
Value    [Maybe]       [Avoid]

MoSCoW Method

• Must Have: Critical for launch
• Should Have: Important but not critical
• Could Have: Nice to have
• Won't Have: Out of scope

Discovery Frameworks

Customer Interview Guide

1. Context Questions (5 min)
   - Role and responsibilities
   - Current workflow
   - Tools used

2. Problem Exploration (15 min)
   - Pain points
   - Frequency and impact
   - Current workarounds

3. Solution Validation (10 min)
   - Reaction to concepts
   - Value perception
   - Willingness to pay

4. Wrap-up (5 min)
   - Other thoughts
   - Referrals
   - Follow-up permission

Hypothesis Template

We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]

Opportunity Solution Tree

Outcome
├── Opportunity 1
│   ├── Solution A
│   └── Solution B
└── Opportunity 2
    ├── Solution C
    └── Solution D

Metrics & Analytics

North Star Metric Framework

• Identify Core Value: What's the #1 value to users?
• Make it Measurable: Quantifiable and trackable
• Ensure It's Actionable: Teams can influence it
• Check Leading Indicator: Predicts business success

Funnel Analysis Template

Acquisition → Activation → Retention → Revenue → Referral

Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations

Feature Success Metrics

• Adoption: % of users using feature
• Frequency: Usage per user per time period
• Depth: % of feature capability used
• Retention: Continued usage over time
• Satisfaction: NPS/CSAT for feature

Best Practices

Writing Great PRDs

• Start with the problem, not solution
• Include clear success metrics upfront
• Explicitly state what's out of scope
• Use visuals (wireframes, flows)
• Keep technical details in appendix
• Version control changes

Effective Prioritization

• Mix quick wins with strategic bets
• Consider opportunity cost
• Account for dependencies
• Buffer for unexpected work (20%)
• Revisit quarterly
• Communicate decisions clearly

Customer Discovery Tips

• Ask "why" 5 times
• Focus on past behavior, not future intentions
• Avoid leading questions
• Interview in their environment
• Look for emotional reactions
• Validate with data

Stakeholder Management

• Identify RACI for decisions
• Regular async updates
• Demo over documentation
• Address concerns early
• Celebrate wins publicly
• Learn from failures openly

Common Pitfalls to Avoid

• Solution-First Thinking: Jumping to features before understanding problems
• Analysis Paralysis: Over-researching without shipping
• Feature Factory: Shipping features without measuring impact
• Ignoring Technical Debt: Not allocating time for platform health
• Stakeholder Surprise: Not communicating early and often
• Metric Theater: Optimizing vanity metrics over real value

Integration Points

This toolkit integrates with:

• Analytics: Amplitude, Mixpanel, Google Analytics
• Roadmapping: ProductBoard, Aha!, Roadmunk
• Design: Figma, Sketch, Miro
• Development: Jira, Linear, GitHub
• Research: Dovetail, UserVoice, Pendo
• Communication: Slack, Notion, Confluence

Quick Commands Cheat Sheet

# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15

# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt

# Create sample data
python scripts/rice_prioritizer.py sample

# JSON outputs for integration
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json

与智能体协作框架集成

本工具包可以与智能体协作框架无缝集成，实现产品团队的智能化协作。

集成场景

场景1: 功能优先级评审会议

将RICE排序工具与多智能体会议决策结合：

# 1. 使用RICE脚本生成初步排序
python scripts/rice_prioritizer.py features.csv --capacity 15

# 2. 调用智能体团队进行会议讨论
"请用产品团队评审以下功能的优先级：[功能列表]"

# 3. 输出包含RICE分数和会议共识的完整决策

参与智能体:

• 产品经理（主持，使用RICE方法）
• 技术架构师（评估实现难度）
• 市场分析师（评估市场价值）
• 财务顾问（评估ROI）

相关技能:

• agent-team: 智能体协作框架
• multi-agent-meeting: 会议决策流程

会议模板: multi-agent-meeting/assets/meeting-templates/product-feature-review.md

场景2: 客户洞察分析会议

将访谈分析工具与智能体团队结合：

# 1. 使用分析脚本提取洞察
python scripts/customer_interview_analyzer.py interview.txt

# 2. 调用智能体团队讨论改进方案
"分析这份访谈记录并生成产品改进方案：[访谈文本]"

# 3. 输出包含洞察、方案和PRD草稿的完整报告

参与智能体:

• 产品经理（方案制定）
• 用户研究员（洞察提取）
• 设计师（体验改进）
• 技术架构师（可行性评估）

相关技能:

• agent-team: 智能体协作框架
• multi-agent-meeting: 会议决策流程

会议模板: multi-agent-meeting/assets/meeting-templates/customer-insight-analysis.md

场景3: 产品路线图规划会议

结合战略分析和RICE排序：

# 1. 战略分析智能体识别市场机会
"扫描AI内容生成领域的市场机会"

# 2. 使用RICE方法对机会进行排序
python scripts/rice_prioritizer.py opportunities.csv --capacity 15

# 3. 召开路线图规划会议
"制定Q2产品路线图，团队容量15人月"

# 4. 输出季度路线图和资源分配计划

参与智能体:

• 产品经理（路线图规划）
• 战略分析智能体（市场机会识别）
• 技术架构师（技术可行性）
• 项目经理（资源和时间评估）

相关技能:

• agent-team: 智能体协作框架（场景9：产品路线图规划会议）

产品经理智能体定义

当在智能体协作框架中使用"产品经理智能体"时，该智能体具备以下能力：

专业知识:

• RICE优先级排序方法
• 客户访谈分析技巧
• PRD文档编写规范
• 产品路线图规划
• 北极星指标定义

工具调用:

# 优先级排序
self.call_tool("rice_prioritizer", features_csv, capacity=15)

# 访谈分析
self.call_tool("customer_interview_analyzer", interview_text)

# PRD生成
self.use_template("prd_templates", template_type="standard")

协作接口:

• 输入: 功能列表、用户反馈、市场分析
• 输出: 优先级排序、PRD文档、产品路线图

适用场景:

• 功能评审会议
• 客户洞察分析
• 产品路线图规划
• 需求文档编写

智能体定义: 参考 agent-team/references/agent-registry.md 中的"产品经理智能体（增强版）"

用户研究员智能体定义

专业知识:

• 客户访谈分析
• 痛点识别和严重程度评估
• 用户画像构建
• Jobs-to-be-Done 分析
• 情感分析和主题提取

工具调用:

# 访谈分析
self.call_tool("customer_interview_analyzer", interview_text, output_format="json")

# 提取关键洞察
insights = self.extract_insights(analysis_result)

协作接口:

• 输入: 访谈记录、用户反馈、行为数据
• 输出: 洞察报告、痛点列表、用户画像

适用场景:

• 客户访谈分析
• 用户需求挖掘
• 产品改进方向识别

智能体定义: 参考 agent-team/references/agent-registry.md 中的"用户研究员智能体"

完整协作示例

用户输入:

我有以下功能需要评审优先级：
1. AI自动生成脚本
2. 多平台发布
3. 数据分析看板
4. 用户协作功能
5. API开放平台

请帮我评审并生成优先级排序，团队容量15人月。

系统执行流程:

• 识别场景: 产品功能优先级评审（agent-team 场景7）

• 组建团队:
• 产品经理（主持）
• 技术架构师
• 市场分析师
• 财务顾问

• 数据准备:

   # 产品经理智能体调用RICE脚本
   python scripts/rice_prioritizer.py features.csv --capacity 15

• 会议讨论 (使用 multi-agent-meeting 流程):

   > 产品经理: 根据RICE排序，AI自动生成脚本得分最高(85分)...
   > 技术架构师: 从技术角度，这个功能可行，可以使用现有大模型...
   > 市场分析师: 市场调研显示，用户对AI功能的需求强烈...
   > 财务顾问: 预计3个月可以回本，ROI较高...

• 决策输出:

   # 功能优先级排序结果
   
   ## 最终排序
   1. AI自动生成脚本 (RICE: 85) - P0
   2. 多平台发布 (RICE: 72) - P1
   3. API开放平台 (RICE: 58) - P2
   
   ## Q2开发计划
   - AI自动生成脚本: 3人月
   - 多平台发布: 2人月
   - 预留缓冲: 1人月

相关资源

智能体协作框架:

• 技能名称: agent-team
• 智能体注册表: agent-team/references/agent-registry.md
• 协作模板: agent-team/references/collaboration-templates.md

会议决策流程:

• 技能名称: multi-agent-meeting
• 会议模板: multi-agent-meeting/assets/meeting-templates/
• 会议记录格式: multi-agent-meeting/references/meeting-record-format.md

产品场景模板:

• 场景7: 产品功能优先级评审会议
• 场景8: 客户访谈洞察分析会议
• 场景9: 产品路线图规划会议
• 场景10: 产品定价策略会议

集成优势

整合前:

• 工具独立使用，需要手动组合
• 缺少多角度专业分析
• 决策过程不透明

整合后:

• ✅ 一键启动完整协作流程
• ✅ 多智能体专业分析
• ✅ 实时展示讨论过程
• ✅ 标准化决策输出
• ✅ 工具自动调用

用户价值:

• 节省时间: 从手动组合到一键启动
• 提升质量: 多角度专业分析
• 降低门槛: 预设模板和流程
• 完整闭环: 从数据分析到决策输出