Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
AI 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 opportuni...
skill openclawclawhub Free
Find profitable business opportunities in any niche by scanning Twitter, web, Reddit, and Product Hunt for unmet needs and pain points. Scores each opportuni...
β¬ 0 downloads β
0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/scoring-guide.md, scripts/scout.py
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- avnikulin35
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
AI Opportunity Scout
Find what people need β evaluate if you can build it β 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
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): Criterion5 (Best)3 (Medium)1 (Worst)Demand50+ people asking10-20 mentions1-2 mentionsCompetitionNo solutions existSome solutions, all flawedSaturated marketFeasibilityBuild MVP in 1-2 days1-2 weeksMonths of workMonetizationPeople actively paying for similarFreemium possibleHard to charge Total Score interpretation: 16-20: π₯ BUILD IT NOW 12-15: π Strong opportunity, worth pursuing 8-11: π€ Monitor, not urgent 4-7: β Skip Detailed scoring examples: see references/scoring-guide.md
Step 4: Generate Report
- Format results as:
- # Opportunity Scout: [Niche] β [Date]
- ## π 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 β easy to replace Crypto/finance niches: high monetization but also high competition Niche down: "AI agent for dentists" beats "AI agent" every time
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs1 Scripts
- SKILL.md
- references/scoring-guide.md
- scripts/scout.py