/product-lens
- 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
$ npx -y skills add loulanyue/awesome-claude-notes --skill product-lens --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/product-lens
Context preview
The summary Claude sees to decide when to auto-load this skill.
- 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
SKILL.md
product-lens.SKILL.mdProduct 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, CLAUDE.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
Read more
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, CLAUDE.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
Community-maintained distribution of reusable AI coding agents, commands, skills, hooks, and cross-harness workflows.
Repo: loulanyue/awesome-claude-notes
Other skills on awesome-claude-notes.
- /agent-eval
Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics
Open skill - /agent-harness-construction
Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
Open skill - /agentic-engineering
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Open skill - /ai-first-engineering
Engineering operating model for teams where AI agents generate a large share of implementation output.
Open skill - /ai-regression-testing
Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code.
Open skill - /android-clean-architecture
Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns.
Open skill

