sales-qualification▌
refoundai/lenny-skills · updated Apr 8, 2026
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Framework-driven approach to identifying and pursuing only sales-qualified leads worth your time.
- ›Focuses on aggressive disqualification and early-stage fit assessment, with the core principle that a clear \"no\" on the first call is a successful outcome
- ›Helps you define explicit disqualification criteria, design discovery questions that reveal fit efficiently, and systematize qualification decisions
- ›Emphasizes that conversion problems usually stem from pursuing wrong leads rather th
Sales Qualification
Help the user qualify sales leads effectively using frameworks from 1 product leader.
How to Help
When the user asks for help with sales qualification:
- Understand current process - Ask how they currently decide which leads to pursue
- Identify disqualification criteria - Help them define what makes a lead NOT worth pursuing
- Design discovery questions - Create questions that efficiently reveal fit
- Build a qualification framework - Help them systematize qualification decisions
Core Principles
Most sales problems are qualification problems
Jen Abel: "It's qualification. Qualification because if you spend your time on the wrong leads, that equates to a zero." If conversion rates are low, the issue is often pursuing leads that were never going to close rather than poor sales execution.
"No" is a successful outcome
Jen Abel: "I am a qualification crazy person. I will not get in on another call with someone because on the first call it's either a yes or a no, there's no in between." The goal of early calls is to determine fit, not to convince. A clear "no" saves time that can be spent on better leads.
Disqualify aggressively
The best salespeople are rigorous about disqualification. They'd rather pursue fewer, better-qualified opportunities than spread themselves thin across mediocre leads.
First call should determine fit
If a lead requires multiple calls before you can determine whether they're a fit, your discovery process is too slow. Qualification should happen early and decisively.
Time is the scarcest resource
Every hour spent on a bad lead is an hour not spent on a good one. The math of sales productivity favors aggressive filtering.
Questions to Help Users
- "What percentage of your pipeline actually closes? Is the problem quality or execution?"
- "What are the characteristics of your best customers? How quickly can you identify those traits?"
- "What questions do you ask in discovery that reveal whether a lead is qualified?"
- "When was the last time you disqualified a lead on the first call?"
- "What would need to be true for you to walk away from a lead earlier?"
Common Mistakes to Flag
- Pursuing all inbound - Treating every lead as equally worthy of time
- Slow qualification - Taking multiple calls to determine what could be known in one
- Hope selling - Continuing to pursue leads you know aren't a fit because the pipeline looks thin
- No disqualification criteria - Not having explicit reasons to say no
- Confusing activity with progress - Measuring calls made rather than qualified opportunities created
Deep Dive
For all 2 insights from 1 guest, see references/guest-insights.md
Related Skills
- product-led-sales
- sales-compensation
- pricing-strategy
How to use sales-qualification 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 sales-qualification
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches sales-qualification 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 sales-qualification. Access the skill through slash commands (e.g., /sales-qualification) 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
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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.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
4.8★★★★★34 reviews- ★★★★★Amina Rao· Dec 28, 2024
sales-qualification has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Ren Zhang· Dec 20, 2024
sales-qualification is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Li Anderson· Dec 20, 2024
sales-qualification reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Shikha Mishra· Dec 16, 2024
Keeps context tight: sales-qualification is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Ren Liu· Nov 19, 2024
We added sales-qualification from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Evelyn Chawla· Nov 19, 2024
Keeps context tight: sales-qualification is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sakura Khan· Nov 11, 2024
Solid pick for teams standardizing on skills: sales-qualification is focused, and the summary matches what you get after install.
- ★★★★★Lucas Iyer· Nov 11, 2024
I recommend sales-qualification for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Rahul Santra· Nov 7, 2024
sales-qualification 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: sales-qualification is focused, and the summary matches what you get after install.
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