Help teams articulate compelling long-term product visions grounded in user outcomes, not features or taglines.
Run in your terminal
Provides frameworks from 101 product leaders (Notion, Airbnb, New York Times) covering four criteria for strong vision: lofty yet realistic, free of current technical constraints, and grounded in a potent user problem
Guides users to describe the user's future world in 5–10 years rather than product features, with emphasis on emotional outcomes and behavioral change
Include
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiondefining-product-visionExecute the skills CLI command in your project's root directory to begin installation:
Package manager
npx skills add https://github.com/refoundai/lenny-skills --skill defining-product-visionFetches defining-product-vision from refoundai/lenny-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 defining-product-vision. Access via /defining-product-visionin 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
Package manager
npx skills add https://github.com/refoundai/lenny-skills --skill defining-product-visionWorks with
2
total installs
2
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616
GitHub stars
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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
greedychipmunk/agent-skills
ailabs-393/ai-labs-claude-skills
Useful defaults in defining-product-vision — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend defining-product-vision for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
defining-product-vision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added defining-product-vision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in defining-product-vision — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added defining-product-vision from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
defining-product-vision fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for defining-product-vision matched our evaluation — installs cleanly and behaves as described in the markdown.
defining-product-vision reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend defining-product-vision for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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