Best use case
product-lens is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Product thinking validation before building features
Teams using product-lens should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/product-lens/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How product-lens Compares
| Feature / Agent | product-lens | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Product thinking validation before building features
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# Product Lens — Think Before You Build ## 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-qa` to verify the user journey audit findings - `/design-system audit` for visual polish assessment - `/canary-watch` for post-launch monitoring
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