Product Agent

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:

{
  "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:

{
  "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.