Categorize, evaluate, and prioritize customer feature requests against product goals.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionanalyze-feature-requestsExecute the skills CLI command in your project's root directory to begin installation:
Fetches analyze-feature-requests from phuryn/pm-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate analyze-feature-requests. Access via /analyze-feature-requests in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
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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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Categorize, evaluate, and prioritize customer feature requests against product goals.
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.
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.
The user will describe their product goal and provide feature requests. Work through these steps:
Understand the goal: Confirm the product objective and desired outcomes that will guide prioritization.
Categorize requests into themes: Group related requests together and name each theme.
Assess strategic alignment: For each theme, evaluate how well it aligns with the stated goals.
Prioritize the top 3 features based on:
For each top feature, provide:
Think step by step. Save as markdown or create a structured output document.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
analyze-feature-requests fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
analyze-feature-requests fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
analyze-feature-requests has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: analyze-feature-requests is focused, and the summary matches what you get after install.
analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
analyze-feature-requests is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: analyze-feature-requests is focused, and the summary matches what you get after install.
Solid pick for teams standardizing on skills: analyze-feature-requests is focused, and the summary matches what you get after install.
analyze-feature-requests reduced setup friction for our internal harness; good balance of opinion and flexibility.
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