scoping-cutting▌
refoundai/lenny-skills · updated Apr 8, 2026
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Help teams scope projects and cut features using frameworks from 15 product leaders.
- ›Teaches appetite-based planning: set fixed time budgets and vary scope instead of extending deadlines
- ›Covers eight core principles including MVP as validation tool, aggressive feature cutting, and the \"build the scooter, not the axle\" approach to end-to-end value
- ›Provides Wizard of Oz testing guidance to validate hypotheses manually before engineering investment
- ›Includes diagnostic questions and
Scoping & Cutting
Help the user scope projects and cut features effectively using frameworks from 15 product leaders.
How to Help
When the user asks for help with scoping:
- Understand the hypothesis - Ask what they're trying to learn or validate
- Identify the appetite - Determine how much time/resources they're willing to invest
- Find the essential core - Help them identify what must be present for the first version
- Design for learning - Ensure the scope enables fast feedback, not just fast shipping
Core Principles
Use appetite, not estimates
Ryan Singer: "We're going to go the other way around and we're going to say, what is the maximum amount of time we're willing to go before we actually finish something?" Set a fixed time budget (appetite) and design a version of the solution that fits within it. Vary scope, not deadlines.
MVP is a validation tool
Eric Ries: "MVP is simply for whatever the hypothesis is that we're trying to test, what is the most efficient way to get the validation we need about whether a hypothesis is true or not?" An MVP is not a low-quality product - it's the most efficient way to test a specific hypothesis.
Cut the list in half, then half again
Eric Ries: "Write out the list of features that are necessary in your MVP. Cut it in half and cut it in half again and build that." Founders consistently overestimate what's "minimum." Aggressive cutting is required to reach a true baseline.
Fixed time, small teams
Jason Fried: "Our appetite for any individual feature is no more than six weeks... So we have to figure out the simplest, most effective version of that to get that done within six weeks and get it done by two people." Constraints force creative solutions. Limit team size to maintain focus.
Build the scooter, not the axle
Eeke de Milliano: "If you're trying to build the minimum viable product for a car, don't build just the wheels and the axle, build the scooter first." An MVP should be a functional, end-to-end version of a smaller value proposition, not an incomplete piece of a larger one.
Use Wizard of Oz testing
Crystal W: "It's really this Wizard of Oz experience. We don't have to build anything. I coordinated with a bunch of interns and we were able to validate some of the value prop." Validate value propositions manually before investing in engineering. Use humans to simulate automated features.
Kill projects that don't finish in time
Jason Fried: "If there's any work that's left over that's still on the left side of the hill, meaning we're still pushing it up, we don't know how we're going to do it and we're at our time limit, it almost certainly dies." Let projects die if they aren't completed within their allotted time to prevent never-ending work.
Build the option to pivot into the process
Paige Costello: "We added into our product process a notion that we might pivot or cut from stuff that we put on our roadmap because it felt like once it was on the roadmap, it had to be done." Formalize the ability to cut or pivot from roadmap items to avoid the sunk cost fallacy.
Questions to Help Users
- "What's the single hypothesis you're trying to validate with this version?"
- "What's the maximum time you're willing to invest before shipping something?"
- "What would you cut if you had to ship in half the time?"
- "Is there a way to test this manually before building automation?"
- "If this feature doesn't ship in time, will you kill it or extend?"
- "What's the smallest thing that still delivers complete value?"
Common Mistakes to Flag
- Estimating instead of time-boxing - Asking "how long will this take?" instead of "what can we do in X weeks?"
- Building the axle - Shipping incomplete parts of a larger feature instead of complete smaller features
- Never killing projects - Extending deadlines instead of cutting scope or canceling
- Over-engineering the MVP - Building too much before testing the core hypothesis
- Ignoring the Wizard of Oz - Always defaulting to building when manual validation would be faster
Deep Dive
For all 19 insights from 15 guests, see references/guest-insights.md
Related Skills
- prioritizing-roadmap
- planning-under-uncertainty
- problem-definition
How to use scoping-cutting on Cursor
AI-first code editor with Composer
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 scoping-cutting
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches scoping-cutting from GitHub repository refoundai/lenny-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate scoping-cutting. Access the skill through slash commands (e.g., /scoping-cutting) 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.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★30 reviews- ★★★★★Lucas Lopez· Dec 12, 2024
Registry listing for scoping-cutting matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Ganesh Mohane· Dec 8, 2024
We added scoping-cutting from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sakshi Patil· Nov 27, 2024
Useful defaults in scoping-cutting — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mia Li· Nov 3, 2024
scoping-cutting reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Mia Perez· Oct 22, 2024
We added scoping-cutting from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chaitanya Patil· Oct 18, 2024
Registry listing for scoping-cutting matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Mateo Yang· Sep 9, 2024
scoping-cutting is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Mia Mensah· Sep 1, 2024
scoping-cutting fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Advait Martinez· Aug 28, 2024
Solid pick for teams standardizing on skills: scoping-cutting is focused, and the summary matches what you get after install.
- ★★★★★Lucas Srinivasan· Aug 20, 2024
scoping-cutting has been reliable in day-to-day use. Documentation quality is above average for community skills.
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