Discover and validate product ideas, analyze markets, scope MVPs, and optimize app store presence for iOS/macOS apps. Use when user asks to discover, validate, assess, scope, or analyze product ideas, market opportunities, or when they mention "product agent", "app idea validation", "should I build this", "MVP", "market analysis", or "ASO".
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---
name: product-agent
description: Discover and validate product ideas, analyze markets, scope MVPs, and optimize app store presence for iOS/macOS apps. Use when user asks to discover, validate, assess, scope, or analyze product ideas, market opportunities, or when they mention "product agent", "app idea validation", "should I build this", "MVP", "market analysis", or "ASO".
allowed-tools: [Read, Write, WebSearch, WebFetch, AskUserQuestion]
last_verified: 2026-07-16
review_by: 2027-06-22
---
# Product Agent Skill
Product Agent validates iOS/macOS app ideas by analyzing problems, markets, and competition. It provides honest, structured assessments to help you decide whether to build.
## When This Skill Activates
Use this Skill when the user wants to:
- Discover or validate product ideas
- Analyze market opportunities
- Check if an app idea is worth building
- Understand competitive landscape
- Assess problem severity
- Get honest feedback on app concepts
## How It Works
This skill performs structured product analysis using reasoning and web research. No external tools required — Claude analyzes the idea directly and researches the market via WebSearch/WebFetch.
## Quick Start
When the user provides an app idea, perform the **Problem Discovery Analysis** below and present the results.
If the user hasn't provided enough detail, ask:
1. What's the app idea? (required)
2. What platform? (iOS, macOS, or both — default: iOS/macOS)
3. Who's the target user? (optional but improves analysis)
## Problem Discovery Analysis
For each idea, analyze and produce these fields:
### 1. Problem Statement
One-sentence description of the core problem the app solves.
### 2. Target Users
Who experiences this problem most acutely? Be specific about demographics, roles, and context.
### 3. Pain Points
List 4-8 specific, concrete pain points users experience today. Each should be observable and verifiable.
### 4. Severity Score (1-10)
Rate how painful this problem is:
- **1-3**: Weak problem, low urgency — users barely notice
- **4-6**: Moderate problem, decent opportunity — users work around it
- **7-8**: Strong problem, good opportunity — users actively seek solutions
- **9-10**: Critical problem, excellent opportunity — users are desperate (rare)
### 5. Frequency
How often do target users encounter this problem? Daily problems are stronger than weekly ones.
### 6. Current Solutions
Research existing alternatives using WebSearch. For each competitor:
- Name and brief description
- Key strengths
- Main limitations
- Pricing model
### 7. Market Opportunity
Assess the opportunity using one of: **WEAK**, **MODERATE**, **STRONG**, **EXCELLENT**.
Include reasoning about market saturation, differentiation potential, and timing.
### 8. Recommendation
The most important field. Provide an honest verdict:
- **BUILD** — Clear opportunity, go for it
- **PROCEED WITH CAUTION** — Opportunity exists but significant risks
- **DO NOT BUILD** — Market saturated, weak problem, or better alternatives exist
Include:
- Specific reasons for the verdict
- Key risks
- What would need to be true for this to succeed
- Alternative approaches if "don't build"
## Output Format
Present results as structured JSON for easy consumption by other skills:
```json
{
"problem_statement": "One-sentence core problem",
"target_users": "Who experiences this problem",
"pain_points": ["List of specific pain points"],
"severity_score": "N/10",
"frequency": "How often users encounter this",
"current_solutions": ["Existing alternatives and their limitations"],
"opportunity": "WEAK|MODERATE|STRONG|EXCELLENT — reasoning",
"recommendation": "Honest verdict with detailed reasoning"
}
```
Follow the JSON with a human-readable summary highlighting the key takeaway.
## Research Process
1. **Analyze the idea** — Break down the problem, users, and value proposition
2. **Search for competitors** — Use WebSearch for "[category] apps iOS", "[competitor] features", "[competitor] pricing"
3. **Check App Store landscape** — Search for similar apps, ratings, reviews
4. **Assess market trends** — Search for "[category] market growth", "[category] trends 2026"
5. **Synthesize findings** — Combine analysis into structured output
## Interpreting Results
### Key Field: `recommendation`
This is the **most important field**. It contains:
- Honest assessment of whether to build
- Market reality check
- Competitive analysis
- Specific reasons for the verdict
**The analysis is brutally honest** — if it says "don't build", there's usually a good reason.
### Severity Score
- **1-3**: Weak problem, low urgency
- **4-6**: Moderate problem, decent opportunity
- **7-8**: Strong problem, good opportunity
- **9-10**: Critical problem, excellent opportunity
### Opportunity Assessment
Look for keywords:
- "WEAK" — Saturated market or marginal problem
- "MODERATE" — Some opportunity with differentiation
- "STRONG" — Clear gap in market
- "EXCELLENT" — Underserved need with high demand
## Common Workflows
### 1. Quick Idea Validation
User provides an idea. Run the full analysis and focus on the `recommendation` and `severity_score`.
**Decision framework:**
- **Score 7+, STRONG opportunity, BUILD verdict** — Green light
- **Score 4-6, MODERATE opportunity, CAUTION verdict** — Needs differentiation strategy
- **Score <4, WEAK opportunity, DON'T BUILD verdict** — Red light
### 2. Comparing Multiple Ideas
Run analysis on each idea, then compare:
- Severity scores (higher = better)
- Opportunity assessments (STRONG > MODERATE > WEAK)
- Recommendation verdicts
- Current solutions (fewer/weaker competitors = better)
### 3. Iterative Refinement
If initial analysis says "don't build", explore pivots:
- Narrow the niche (e.g., "note-taking" -> "note-taking for academic researchers")
- Change the target user
- Add a unique angle (e.g., AI-powered, privacy-focused)
Re-run analysis for each pivot and look for improving severity and opportunity scores.
## After Running Discovery
1. **Highlight the recommendation** — this is what the user cares about most
2. **Explain the severity score** — put it in context
3. **Summarize pain points** — these validate the problem
4. **Discuss opportunity** — is the market good?
5. **Present alternatives** — if "don't build", what should they do instead?
## Deep-Dive Skills
After running discovery, use these specialized Skills for deeper analysis:
### **competitive-analysis** Skill
When discovery shows potential and you need to understand competition in detail:
- Feature comparison matrices
- Pricing analysis across competitors
- SWOT for each competitor
- Differentiation opportunities
### **market-research** Skill
When discovery shows potential and you need to size the opportunity:
- TAM/SAM/SOM calculations
- Growth trends and projections
- Market maturity assessment
- Revenue potential estimates
**Workflow:**
```
1. product-agent → Quick validation (problem discovery)
2. If promising, use deep-dive Skills:
- competitive-analysis → Understand players
- market-research → Size opportunity
3. Make go/no-go decision with full data
```
## Example
**User asks:** "Should I build a password manager for the Apple ecosystem?"
**You research and analyze**, then present:
```json
{
"problem_statement": "Users need secure password management that seamlessly integrates across Apple devices without relying on third-party services.",
"target_users": "Apple ecosystem loyalists who own multiple Apple devices and prioritize privacy and native integration.",
"pain_points": [
"Existing password managers prioritize cross-platform over deep Apple integration",
"Third-party managers don't fully integrate with iOS autofill and Face ID",
"Subscription fatigue from cross-platform services they don't need",
"UIs that don't follow Apple Human Interface Guidelines"
],
"severity_score": "3/10",
"frequency": "Daily, but existing solutions work adequately",
"current_solutions": [
"iCloud Keychain - Free, deeply integrated, improving rapidly. Limited organization.",
"1Password - Polished, $36-48/year, cross-platform focused",
"Bitwarden - Open source, cheaper, generic UI"
],
"opportunity": "WEAK - Highly saturated market with Apple's own iCloud Keychain as dominant free incumbent. Any differentiating feature risks being absorbed by Apple in the next OS update.",
"recommendation": "DO NOT BUILD. Apple's iCloud Keychain is free, pre-installed, and continuously improving. The differentiation window is tiny, willingness to pay for marginal improvements is low, and one security breach would be catastrophic for an indie developer. Consider instead: tools that augment iCloud Keychain, niche password management (API keys for developers), or a different underserved problem in the Apple ecosystem."
}
```
**Summary:** This is not recommended. iCloud Keychain dominates as a free, deeply-integrated solution. Unless you have a truly novel approach or serve a specific underserved niche, the market is too saturated.
## Tips for Effective Use
1. **Be specific in idea descriptions** — More detail = better analysis
2. **Trust the recommendation** — The analysis is designed to be honest
3. **Look for patterns** — Similar apps getting "don't build" = saturated market
4. **Focus on severity + opportunity** — Both must be strong
5. **Read current_solutions** — Shows what you're competing against
6. **Save your analyses** — Build a knowledge base of validated/invalidated ideas
---
**Remember:** This analysis is brutally honest. If it says "don't build", listen. It's saving you months of wasted effort on weak ideas.