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/product-manager-toolkit

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

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lihongwei-cn
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$ npx -y skills add LiHongwei-cn/lihongwei-cn --skill product-manager-toolkit --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/product-manager-toolkit

Context preview

The summary Claude sees to decide when to auto-load this skill.

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

SKILL.md

product-manager-toolkit.SKILL.md
name: product-manager-toolkit
description: "Essential tools and frameworks for modern product management, from discovery to delivery."
risk: unknown
source: community
date_added: "2026-02-27"

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

1. Choose template from `references/prd_templates.md` 2. Fill in sections based on discovery work 3. Review with stakeholders 4. Version control in your PM tool

Core Workflows

Feature Prioritization Process

1. **Gather Feature Requests**

  • Customer feedback
  • Sales requests
  • Technical debt
  • Strategic initiatives

2. **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)

3. **Analyze Portfolio**

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

4. **Generate Roadmap**

  • Quarterly capacity planning
  • Dependency mapping
  • Stakeholder alignment

Customer Discovery Process

1. **Conduct Interviews**

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

2. **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

3. **Synthesize Findings**

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

4. **Validate Solutions**

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

PRD Development Process

1. **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

2. **Structure Content**

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

3. **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:

1. **Standard PRD Template**

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

2. **One-Page PRD**

  • Concise format for quick alignment
  • Focus on problem/solution/metrics
  • Good for smaller features

3. **Agile Epic Template**

  • Sprint-based delivery
  • User story mapping
  • Acceptance criteria focus

4. **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

1. **Identif

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