Hackd - Hacker Matching Platform

Overview

Problem: Finding teammates at hackathons is difficult. Slack channels get crowded and reaching out is awkward.

Solution: Hackd analyzes GitHub profiles and matches hackers using sentiment and code analysis.

Features

• GitHub profile and coding pattern analysis
• AI-powered matching using Cohere
• Recruiter dashboard
• Collaboration scoring
• Clean React interface

Architecture

hackd/
├── backend/
│   ├── api/main.py
│   ├── github-analyzer/github_analyzer.py
│   ├── matching/matcher.py
│   └── requirements.txt
├── frontend/hackd-web/
│   ├── app/{matching,recruiting,hacker}/
│   ├── convex/
│   └── lib/api.ts
└── config/docker-compose.yml

Quick Start

Prerequisites

• Node.js 18+
• Python 3.11+
• Git
• GitHub Personal Access Token
• Cohere API Key

Setup

git clone https://github.com/your-username/hackd.git
cd hackd

# Backend
cd backend
pip install -r requirements.txt

# Frontend
cd ../frontend/hackd-web
npm install

Configuration

Backend

cp .env.example .env
# Edit with keys

Frontend

cp .env.local.example .env.local
# Edit with keys

API Keys Needed

Service	Use
GitHub	Profile analysis
Cohere	Matching
Convex	Auth and DB

Run

Dev Mode

# Terminal 1
cd backend
python api/main.py

# Terminal 2
cd frontend/hackd-web
npm run dev

Docker

cd config
docker-compose up --build

Access at http://localhost:3000

API Endpoints

Endpoint	Method	Description
/health	GET	Health check
/api/analyze-github	POST	GitHub profile analysis
/api/match-users	POST	Match hackers
/api/analyze-job-description	POST	Job parsing
/api/analyze-sentiment	POST	Sentiment

Example

const res = await fetch('http://localhost:5000/api/analyze-github', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify({ username: 'octocat' })
});
const data = await res.json();
console.log(data.top_technologies);

Matching Logic

match_score = (
    tech_complementarity * 0.4 +
    experience_compatibility * 0.3 +
    collaboration_compatibility * 0.2 +
    activity_level * 0.1
)