product-strategist

borghei/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/borghei/claude-skills --skill product-strategist
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summary

Strategic toolkit for Head of Product to drive vision, alignment, and organizational excellence.

skill.md

Product Strategist

Strategic toolkit for Head of Product to drive vision, alignment, and organizational excellence.


Table of Contents


Quick Start

Generate OKRs for Your Team

# Growth strategy with default teams
python scripts/okr_cascade_generator.py growth

# Retention strategy with custom teams
python scripts/okr_cascade_generator.py retention --teams "Engineering,Design,Data"

# Revenue strategy with 40% product contribution
python scripts/okr_cascade_generator.py revenue --contribution 0.4

# Export as JSON for integration
python scripts/okr_cascade_generator.py growth --json > okrs.json

Core Capabilities

Capability Description Tool
OKR Cascade Generate aligned OKRs from company to team level okr_cascade_generator.py
Alignment Scoring Measure vertical and horizontal alignment Built into generator
Strategy Templates 5 pre-built strategy types Growth, Retention, Revenue, Innovation, Operational
Team Configuration Customize for your org structure --teams flag

Workflow: Strategic Planning Session

A step-by-step guide for running a quarterly strategic planning session.

Step 1: Define Strategic Focus

Choose the primary strategy type based on company priorities:

Strategy When to Use
Growth Scaling user base, market expansion
Retention Reducing churn, improving LTV
Revenue Increasing ARPU, new monetization
Innovation Market differentiation, new capabilities
Operational Improving efficiency, scaling operations

See references/strategy_types.md for detailed guidance on each strategy.

Step 2: Gather Input Metrics

Collect current state metrics to inform OKR targets:

# Example metrics JSON
{
  "current": 100000,      # Current MAU
  "target": 150000,       # Target MAU
  "current_nps": 40,      # Current NPS
  "target_nps": 60        # Target NPS
}

Step 3: Configure Team Structure

Define the teams that will receive cascaded OKRs:

# Default teams
python scripts/okr_cascade_generator.py growth

# Custom teams for your organization
python scripts/okr_cascade_generator.py growth --teams "Core,Platform,Mobile,AI"

Step 4: Generate OKR Cascade

Run the generator to create aligned OKRs:

python scripts/okr_cascade_generator.py growth --contribution 0.3

Step 5: Review Alignment Scores

Check the alignment scores in the output:

Score Target Action
Vertical Alignment >90% Ensure all objectives link to parent
Horizontal Alignment >75% Check for team coordination
Coverage >80% Validate all company OKRs are addressed
Balance >80% Redistribute if one team is overloaded
Overall >80% Good alignment; <60% needs restructuring

Step 6: Refine and Validate

Before finalizing:

  • Review generated objectives with stakeholders
  • Adjust team assignments based on capacity
  • Validate contribution percentages are realistic
  • Ensure no conflicting objectives across teams
  • Set up tracking cadence (bi-weekly check-ins)

Step 7: Export and Track

Export OKRs for your tracking system:

# JSON for tools like Lattice, Ally, Workboard
python scripts/okr_cascade_generator.py growth --json > q1_okrs.json

OKR Cascade Generator

Automatically cascades company OKRs down to product and team levels with alignment tracking.

Usage

python scripts/okr_cascade_generator.py [strategy] [options]

Strategies:

  • growth - User acquisition and market expansion
  • retention - Customer value and churn reduction
  • revenue - Revenue growth and monetization
  • innovation - Product differentiation and leadership
  • operational - Efficiency and organizational excellence

Configuration Options

Option Description Default
--teams, -t Comma-separated team names Growth,Platform,Mobile,Data
--contribution, -c Product contribution to company OKRs (0-1) 0.3 (30%)
--json, -j Output as JSON instead of dashboard False
--metrics, -m Metrics as JSON string Sample metrics

Examples:

# Custom teams
python scripts/okr_cascade_generator.py retention \
  --teams "Engineering,Design,Data,Growth"

# Higher product contribution
python scripts/okr_cascade_generator.py revenue --contribution 0.4

# Full customization
python scripts/okr_cascade_generator.py innovation \
  --teams "Core,Platform,ML" \
  --contribution 0.5 \
  --json

Input/Output Examples

Example 1: Growth Strategy (Dashboard Output)

Command:

python scripts/okr_cascade_generator.py growth

Output:

============================================================
OKR CASCADE DASHBOARD
Quarter: Q1 2025
Strategy: GROWTH
Teams: Growth, Platform, Mobile, Data
Product Contribution: 30%
============================================================

🏢 COMPANY OKRS

📌 CO-1: Accelerate user acquisition and market expansion
   └─ CO-1-KR1: Increase MAU from 100000 to 150000
   └─ CO-1-KR2: Achieve 150000% MoM growth rate
   └─ CO-1-KR3: Expand to 150000 new markets

📌 CO-2: Achieve product-market fit in new segments
   └─ CO-2-KR1: Reduce CAC by 150000%
   └─ CO-2-KR2: Improve activation rate to 150000%
   └─ CO-2-KR3: Increase MAU from 100000 to 150000

📌 CO-3: Build sustainable growth engine
   └─ CO-3-KR1: Achieve 150000% MoM growth rate
   └─ CO-3-KR2: Expand to 150000 new markets
   └─ CO-3-KR3: Reduce CAC by 150000%

🚀 PRODUCT OKRS

📌 PO-1: Build viral product features and market expansion
   ↳ Supports: CO-1
   └─ PO-1-KR1: Increase product MAU from 100000 to 45000.0
   └─ PO-1-KR2: Achieve 45000.0% feature adoption rate

📌 PO-2: Validate product hypotheses in new segments
   ↳ Supports: CO-2
   └─ PO-2-KR1: Reduce product onboarding efficiency by 45000.0%
   └─ PO-2-KR2: Improve activation rate to 45000.0%

📌 PO-3: Create product-led growth loops engine
   ↳ Supports: CO-3
   └─ PO-3-KR1: Achieve 45000.0% feature adoption rate
   └─ PO-3-KR2: Expand to 45000.0 new markets

👥 TEAM OKRS

Growth Team:
  📌 GRO-1: Build viral product features through acquisition and activation
     └─ GRO-1-KR1: [Growth] Increase product MAU from 100000 to 11250.0
     └─ GRO-1-KR2: [Growth] Achieve 11250.0% feature adoption rate

Platform Team:
  📌 PLA-1: Build viral product features through infrastructure and reliability
     └─ PLA-1-KR1: [Platform] Increase product MAU from 100000 to 11250.0
     └─ PLA-1-KR2: [Platform] Achieve 11250.0% feature adoption rate


📊 ALIGNMENT MATRIX

Company → Product → Teams
----------------------------------------

CO-1
  ├─ PO-1
    └─ GRO-1 (Growth)
    └─ PLA-1 (Platform)

CO-2
  ├─ PO-2

CO-3
  ├─ PO-3


🎯 ALIGNMENT SCORES
----------------------------------------
✓ Vertical Alignment: 100.0%
! Horizontal Alignment: 75.0%
✓ Coverage: 100.0%
✓ Balance: 97.5%
✓ Overall: 94.0%

✅ Overall alignment is GOOD (≥80%)

Example 2: JSON Output

Command:

python scripts/okr_cascade_generator.py retention --json

Output (truncated):

{
  "quarter": "Q1 2025",
  "strategy": "retention",
  "company": {
    "level": "Company",
    "objectives": [
      {
        "id": "CO-1",
        "title": "Create lasting customer value and loyalty",
        "owner": "CEO",
        "key_results": [
          {
            "id": "CO-1-KR1",
            "title": "Improve retention from 100000% to 150000%",
            "current": 100000,
            "target": 150000
          }
        ]
      }
    ]
  },
  "product": {
    "level": "Product",
    "contribution": 0.3,
    "objectives": [...]
  },
  "teams": [...],
  "alignment_scores": {
    "vertical_alignment": 100.0,
    "horizontal_alignment": 75.0,
    "coverage": 100.0,
    "balance": 97.5,
    "overall": 94.0
  },
  "config": {
    "teams": ["Growth", "Platform", "Mobile", "Data"],
    "product_contribution": 0.3
  }
}

See references/examples/sample_growth_okrs.json for a complete example.


Reference Documents

Document Description
references/okr_framework.md OKR methodology, writing guidelines, alignment scoring
references/strategy_types.md Detailed breakdown of all 5 strategy types with examples
references/examples/sample_growth_okrs.json Complete sample output for growth strategy

Best Practices

OKR Cascade

  • Limit to 3-5 objectives per level
  • Each objective should have 3-5 key res
how to use product-strategist

How to use product-strategist on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add product-strategist
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/borghei/claude-skills --skill product-strategist

The skills CLI fetches product-strategist from GitHub repository borghei/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/product-strategist

Reload or restart Cursor to activate product-strategist. Access the skill through slash commands (e.g., /product-strategist) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.638 reviews
  • Liam Tandon· Dec 20, 2024

    product-strategist has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ganesh Mohane· Dec 16, 2024

    Useful defaults in product-strategist — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Mei Shah· Dec 8, 2024

    I recommend product-strategist for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chen Park· Nov 27, 2024

    Solid pick for teams standardizing on skills: product-strategist is focused, and the summary matches what you get after install.

  • Tariq Robinson· Nov 11, 2024

    Useful defaults in product-strategist — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Rahul Santra· Nov 7, 2024

    product-strategist has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Pratham Ware· Oct 26, 2024

    Solid pick for teams standardizing on skills: product-strategist is focused, and the summary matches what you get after install.

  • Evelyn Agarwal· Oct 18, 2024

    product-strategist has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Chen Abebe· Oct 2, 2024

    I recommend product-strategist for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Chen Choi· Sep 21, 2024

    product-strategist reduced setup friction for our internal harness; good balance of opinion and flexibility.

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