Product Lens — Think Before You Build
SkillAI & modelsProduct thinking validation before building features
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Product Lens — Think Before You Build skill
What this skill tells your AI
The instructions your AI receives, as published by jamkris/everything-gemini-code in skills/product-lens/SKILL.md and read by ahel’s review.
When to Use
- Before starting any feature — validate the "why"
- Weekly product review — are we building the right thing?
- When stuck choosing between features
- Before a launch — sanity check the user journey
- When converting a vague idea into a spec
How It Works
Mode 1: Product Diagnostic
Like YC office hours but automated. Asks the hard questions:
1. Who is this for? (specific person, not "developers")
2. What's the pain? (quantify: how often, how bad, what do they do today?)
3. Why now? (what changed that makes this possible/necessary?)
4. What's the 10-star version? (if money/time were unlimited)
5. What's the MVP? (smallest thing that proves the thesis)
6. What's the anti-goal? (what are you explicitly NOT building?)
7. How do you know it's working? (metric, not vibes)
Output: a PRODUCT-BRIEF.md with answers, risks, and a go/no-go recommendation.
Mode 2: Founder Review
Reviews your current project through a founder lens:
1. Read README, GEMINI.md, package.json, recent commits
2. Infer: what is this trying to be?
3. Score: product-market fit signals (0-10)
- Usage growth trajectory
- Retention indicators (repeat contributors, return users)
- Revenue signals (pricing page, billing code, Stripe integration)
- Competitive moat (what's hard to copy?)
4. Identify: the one thing that would 10x this
5. Flag: things you're building that don't matter
Mode 3: User Journey Audit
Maps the actual user experience:
1. Clone/install the product as a new user
2. Document every friction point (confusing steps, errors, missing docs)
3. Time each step
4. Compare to competitor onboarding
5. Score: time-to-value (how long until the user gets their first win?)
6. Recommend: top 3 fixes for onboarding
Mode 4: Feature Prioritization
When you have 10 ideas and need to pick 2:
1. List all candidate features
2. Score each on: impact (1-5) × confidence (1-5) ÷ effort (1-5)
3. Rank by ICE score
4. Apply constraints: runway, team size, dependencies
5. Output: prioritized roadmap with rationale
Output
All modes output actionable docs, not essays. Every recommendation has a specific next step.
Integration
Pair with:
/browser-qato verify the user journey audit findings/design-system auditfor visual polish assessment/canary-watchfor post-launch monitoring
Signals
- GitHub stars
- 87
- Forks
- 22
- Last commit
- May 2026
Advanced
- Catalog kind
- skill
- Gateway key
product-lens- Source
- github.com/jamkris/everything-gemini-code