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/product-agent

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

From plugin
rshankras-apple-skills
848181 skills

Claude Code

$ npx -y skills add rshankras/claude-code-apple-skills --skill product-agent --agent claude-code

SKILL.md

product-agent.SKILL.md
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:

{
  "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.

Read more
@rshankras
Ships withrshankras-apple-skills

A collection of Claude Code skills for iOS, macOS, watchOS, visionOS, and Apple platform development. These skills help you plan and build apps, maintain code quality, ensure HIG compliance, and guide you from idea to App Store.

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Questions about product-agent.

Which coding agents can use product-agent?
product-agent installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.