AI Opportunity Scout

Find what people need → evaluate if you can build it → decide if it's worth it.

Quick Start

When the user specifies a niche (e.g. "AI agents", "crypto trading", "SaaS tools"):

1. 1. Run the scout pipeline below
2. Score each finding with INLINECODE0
3. Present the ranked report

Scout Pipeline

Step 1: Gather Data (use your built-in tools)

Run these searches, adapting queries to the user's niche:

Twitter (via exec):
CODEBLOCK0

Web (via web_search tool):

• - INLINECODE1
• INLINECODE2
• INLINECODE3
• INLINECODE4

ClawHub (if niche is AI/agent related):
CODEBLOCK1

Step 2: Identify Opportunities

From the raw data, extract distinct opportunities. Each opportunity = a specific unmet need that could become a product. Look for:

• - Repeated complaints/requests (same problem mentioned 3+ times)
• Gaps between what exists and what people want
• Problems with existing solutions (too expensive, too complex, missing features)
• Emerging trends without established solutions

Step 3: Score Each Opportunity

Run the scoring script:
CODEBLOCK2

Or score manually using these criteria (1-5 each):

Total Score interpretation:

• - 16-20: 🔥 BUILD IT NOW
• 12-15: 👍 Strong opportunity, worth pursuing
• 8-11: 🤔 Monitor, not urgent
• 4-7: ❌ Skip

Detailed scoring examples: see INLINECODE5

Step 4: Generate Report

Format results as:

CODEBLOCK3

Depth Modes

• - --depth quick: 2 Twitter + 2 web searches. Fast scan, ~2 min.
• INLINECODE7: 4 Twitter + 4 web + ClawHub. Standard, ~5 min.
• INLINECODE8: 6 Twitter + 8 web + ClawHub + Reddit deep dive. Thorough, ~10 min.

Tips

• - Focus on problems people PAY to solve, not just complain about
• "I wish..." and "Does anyone know a tool for..." = strongest signals
• Check if existing solutions are abandoned/unmaintained — easy to replace
• Crypto/finance niches: high monetization but also high competition
• Niche down: "AI agent for dentists" beats "AI agent" every time