analyze-feature-requests

phuryn/pm-skills · updated Apr 8, 2026

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$npx skills add https://github.com/phuryn/pm-skills --skill analyze-feature-requests
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summary

Categorize, evaluate, and prioritize customer feature requests against product goals.

skill.md

Analyze Feature Requests

Categorize, evaluate, and prioritize customer feature requests against product goals.

Context

You are analyzing feature requests for $ARGUMENTS.

If the user provides files (spreadsheets, CSVs, or documents with feature requests), read and analyze them directly. If data is in a structured format, consider creating a summary table.

Domain Context

Never allow customers to design solutions. Prioritize opportunities (problems), not features. Use Opportunity Score (Dan Olsen) to evaluate customer-reported problems: Opportunity Score = Importance × (1 − Satisfaction), normalized to 0–1. See the prioritization-frameworks skill for full details and templates.

Instructions

The user will describe their product goal and provide feature requests. Work through these steps:

  1. Understand the goal: Confirm the product objective and desired outcomes that will guide prioritization.

  2. Categorize requests into themes: Group related requests together and name each theme.

  3. Assess strategic alignment: For each theme, evaluate how well it aligns with the stated goals.

  4. Prioritize the top 3 features based on:

    • Impact: Customer value and number of users affected
    • Effort: Development and design resources required
    • Risk: Technical and market uncertainty
    • Strategic alignment: Fit with product vision and goals
  5. For each top feature, provide:

    • Rationale (customer needs, strategic alignment)
    • Alternative solutions worth considering
    • High-risk assumptions
    • How to test those assumptions with minimal effort

Think step by step. Save as markdown or create a structured output document.


Further Reading

how to use analyze-feature-requests

How to use analyze-feature-requests 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 analyze-feature-requests
2

Execute installation command

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

$npx skills add https://github.com/phuryn/pm-skills --skill analyze-feature-requests

The skills CLI fetches analyze-feature-requests from GitHub repository phuryn/pm-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/analyze-feature-requests

Reload or restart Cursor to activate analyze-feature-requests. Access the skill through slash commands (e.g., /analyze-feature-requests) 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

4.656 reviews
  • Emma Menon· Dec 28, 2024

    analyze-feature-requests fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Nikhil Ndlovu· Dec 20, 2024

    analyze-feature-requests fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Emma Tandon· Dec 4, 2024

    analyze-feature-requests has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Noor Chen· Nov 23, 2024

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

  • Amelia Gill· Nov 19, 2024

    analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Yusuf Wang· Nov 11, 2024

    analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Noor Nasser· Oct 14, 2024

    analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Amelia Rao· Oct 10, 2024

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

  • Yusuf Thompson· Oct 2, 2024

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

  • Noor Tandon· Sep 25, 2024

    analyze-feature-requests reduced setup friction for our internal harness; good balance of opinion and flexibility.

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