A tool that analyzes GitHub profiles to identify investment-worthy projects. It uses AI to evaluate repositories through the lens of venture capital.

This tool solves a specific problem: VCs and angels spend too much time manually reviewing GitHub profiles. It automates the initial screening by analyzing code repositories for commercial potential.

The analysis focuses on what matters for investment: market size, technical moat, team capability, and traction signals. Not just star counts.

Clone the repository:

git clone https://github.com/Siddhant-K-code/github-venture-scout.git
cd github-venture-scout

Install dependencies:

pip install -r requirements.txt

Set up credentials:

cp .env.example .env

Edit .env:

GITHUB_TOKEN=your_github_personal_access_token_here  # Optional
GEMINI_API_KEY=your_gemini_api_key_here              # Required

1. GitHub Settings → Developer settings → Personal access tokens
2. Generate new token (classic)
3. Select scopes: public_repo, read:user

Without token: 60 requests/hour. With token: 5,000 requests/hour.

1. Visit Google AI Studio
2. Get API Key

Run:

python enhanced_analyzer.py

You'll be prompted for:

1. GitHub username
2. Analysis focus (1-5)
3. Analysis depth
4. Minimum stars filter
5. Maximum repositories

1. All repositories - Complete portfolio analysis
2. Most popular - Top 10 by stars
3. Recently active - Last 10 updated (fastest, ~20 repos fetched)
4. Top 20 - Top 20 by stars
5. Actively maintained - Updated in last 6 months (~50 repos fetched)

Default to mode 3 or 5 for speed. Modes 2 and 4 require fetching all repositories.

Two files are generated:

Markdown Report (report_username_timestamp.md)

• Investment opportunities ranked by potential
• Developer profile assessment
• Specific next steps for funding readiness

JSON Report (report_username_timestamp.json)

• Structured data for programmatic use
• Complete analysis metadata

The tool evaluates eight factors:

1. Problem-Solution Fit
2. Market Size (TAM/SAM/SOM)
3. Technical Innovation
4. Competitive Advantage
5. Team Capability
6. Traction Indicators
7. Monetization Potential
8. Scalability

These mirror what VCs actually look for, not what developers think they look for.

Smart fetching minimizes API calls:

• "Recently Active" fetches ~20 repos
• "Actively Maintained" fetches ~50 repos
• "Popular" modes require all repos

With GitHub token: 80x more API calls allowed.

github-venture-scout/
├── enhanced_analyzer.py    # Main code
├── requirements.txt         # Dependencies
├── .env.example            # Environment template
├── .env                    # Your credentials
├── .gitignore
├── README.md
└── report_*.md/json       # Generated reports

User not found: Check username spelling and profile visibility.

Rate limit exceeded: Add GitHub token or wait for reset.

No repositories found: Adjust filters or check if user has public repos.

• VCs: Pre-screen technical founders
• Angels: Quick technical due diligence
• Developers: Self-assessment before fundraising
• Accelerators: Evaluate applicants at scale

Most developer tools optimize for developers. This one optimizes for investors.

It answers the question investors actually ask: "Can this make money?" Not "Is this technically impressive?"

The difference matters. A technically mediocre solution to a billion-dollar problem beats a brilliant solution to a non-problem.

@Siddhant-K-code

This tool provides analysis, not investment advice. Do your own diligence.