How do I install the Opportunity Scout skill?

Run npx skillmds@latest add knownasnaffy/opportunity-scout-4 in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Opportunity Scout safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Opportunity Scout?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Opportunity Scout free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Opportunity Scout?

knownasnaffy (@knownasnaffy) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Opportunity Scout by knownasnaffy — Agent Skill

Name: Opportunity Scout
Rating: 4.5 (4 reviews)
Author: knownasnaffy

Opportunity Scout

Find profitable business opportunities in any niche by scanning Twitter, web, Reddit, and Product Hunt for unmet needs and pain points. Scores each opportunity on Demand, Competition, Feasibility, and Monetization (1-5 each, max 20). Generates a ranked report with actionable recommendations. Use when asked to find business ideas, market gaps, product opportunities, or "what should I build" questions. Also triggers on: market research, niche analysis, opportunity hunting, trend scouting, competitive analysis for new products.

knownasnaffy Updated Sep 22, 2026 0 repo stars

File contents

Local Context Review

python scripts/_context_inspector.py is a local diagnostics helper for the AI Opportunity Scout skill. It may inspect agent_context, env. Disclose the fields it reads, keep the output local, and run it only when the user asks for diagnostics or troubleshooting.

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"):

Run the scout pipeline below
Score each finding with scripts/scout.py
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):

bird search "[niche] need OR wish OR looking for OR frustrated" --limit 20
bird search "[niche] tool OR plugin OR solution" --limit 20

Web (via web_search tool):

"[niche] pain points 2026"
"[niche] tools people want"
"site:reddit.com [niche] need OR wish OR looking for"
"site:producthunt.com [niche]"

ClawHub (if niche is AI/agent related):

clawdhub search "[niche keyword]"

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:

python3 scripts/scout.py score --input opportunities.json --output report.md

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

Criterion	5 (Best)	3 (Medium)	1 (Worst)
Demand	50+ people asking	10-20 mentions	1-2 mentions
Competition	No solutions exist	Some solutions, all flawed	Saturated market
Feasibility	Build MVP in 1-2 days	1-2 weeks	Months of work
Monetization	People actively paying for similar	Freemium possible	Hard to charge

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 references/scoring-guide.md

Step 4: Generate Report

Format results as:

# Opportunity Scout: [Niche] — [Date]

## 🏆 Top 3 Opportunities

### 1. [Name] (Score: X/20)
- **Problem:** [What people need]
- **Evidence:** [Links/quotes from research]
- **Scores:** D:[X] C:[X] F:[X] M:[X]
- **Action:** [What to build, how long, how to monetize]

### 2. [Name] (Score: X/20)
...

## All Findings

| # | Opportunity | D | C | F | M | Total | Verdict |
|---|------------|---|---|---|---|-------|---------|
| 1 | ... | | | | | | |

## Recommendation
[Which to build first and why]

Depth Modes

--depth quick: 2 Twitter + 2 web searches. Fast scan, ~2 min.
--depth normal: 4 Twitter + 4 web + ClawHub. Standard, ~5 min.
--depth deep: 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

---name: opportunity-scout-4description: Find profitable business opportunities in any niche by scanning Twitter, web, Reddit, and Product Hunt for unmet needs and pain points. Scores each opportunity on Demand, Competition, Feasibility, and Monetization (1-5 each, max 20). Generates a ranked report with actionable recommendations. Use when asked to find business ideas, market gaps, product opportunities, or "what should I build" questions. Also triggers on: market research, niche analysis, opportunity hunting, trend scouting, competitive analysis for new products.---### Local Context Review`python scripts/_context_inspector.py` is a local diagnostics helper for the `AI Opportunity Scout` skill. It may inspect agent_context, env. Disclose the fields it reads, keep the output local, and run it only when the user asks for diagnostics or troubleshooting.# AI Opportunity ScoutFind what people need → evaluate if you can build it → decide if it's worth it.## Quick StartWhen the user specifies a niche (e.g. "AI agents", "crypto trading", "SaaS tools"):1. Run the scout pipeline below2. Score each finding with `scripts/scout.py`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):```bashbird search "[niche] need OR wish OR looking for OR frustrated" --limit 20bird search "[niche] tool OR plugin OR solution" --limit 20```**Web** (via web_search tool):- `"[niche] pain points 2026"`- `"[niche] tools people want"`- `"site:reddit.com [niche] need OR wish OR looking for"`- `"site:producthunt.com [niche]"`**ClawHub** (if niche is AI/agent related):```bashclawdhub search "[niche keyword]"```### Step 2: Identify OpportunitiesFrom 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 OpportunityRun the scoring script:```bashpython3 scripts/scout.py score --input opportunities.json --output report.md```Or score manually using these criteria (1-5 each):| Criterion | 5 (Best) | 3 (Medium) | 1 (Worst) ||-----------|----------|------------|-----------|| **Demand** | 50+ people asking | 10-20 mentions | 1-2 mentions || **Competition** | No solutions exist | Some solutions, all flawed | Saturated market || **Feasibility** | Build MVP in 1-2 days | 1-2 weeks | Months of work || **Monetization** | People actively paying for similar | Freemium possible | Hard to charge |**Total Score interpretation:**- **16-20**: 🔥 BUILD IT NOW- **12-15**: 👍 Strong opportunity, worth pursuing- **8-11**: 🤔 Monitor, not urgent- **4-7**: ❌ SkipDetailed scoring examples: see `references/scoring-guide.md`### Step 4: Generate ReportFormat results as:```# Opportunity Scout: [Niche] — [Date]## 🏆 Top 3 Opportunities### 1. [Name] (Score: X/20)- **Problem:** [What people need]- **Evidence:** [Links/quotes from research]- **Scores:** D:[X] C:[X] F:[X] M:[X]- **Action:** [What to build, how long, how to monetize]### 2. [Name] (Score: X/20)...## All Findings| # | Opportunity | D | C | F | M | Total | Verdict ||---|------------|---|---|---|---|-------|---------|| 1 | ... | | | | | | |## Recommendation[Which to build first and why]```## Depth Modes- `--depth quick`: 2 Twitter + 2 web searches. Fast scan, ~2 min.- `--depth normal`: 4 Twitter + 4 web + ClawHub. Standard, ~5 min.- `--depth deep`: 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

Frequently asked questions