SlackSearch

Mini-project consisting of ingesting Slack user identities to trigger off an OSINT crawler, piping the packaged JSON to a Supabase endpoint. We cache and query records to then interface the database to create a sleek UI providing likelihoods of same users existing elsewhere on the web.

Repository Structure

This repository is divided into three distinct domains. Please work only within your assigned directory unless coordinating integration.

/project-root
│
├── /ingestor (Kellen)
│   ├── /src                 # Python/Node scripts for Slack API 
│   ├── /output              # Local storage for raw JSON dumps (GitIgnored)
│   └── Dockerfile           # Environment setup 
│
├── /backend (Aadi)
│   ├── /supabase
│   │   ├── /functions       # Edge Functions for data ingestion and scoring logic
│   │   └── /migrations      # SQL Schema definitions
│   └── types.ts             # TypeScript definitions matching schema.json
│
├── /web-client (Dilworth)
│   ├── /src
│   │   ├── /components      # React components (MatchCard, Dashboard)
│   │   └── /pages           # Next.js App Router pages
│   ├── package.json
│   └── tailwind.config.js
│
├── schema.json              
├── dummy_data.json
└── README.md

The Data Pipeline

1. Ingestor fetches Slack User List -> Runs OSINT -> Outputs JSON matching schema.json.
2. Ingestor POSTs JSON to Backend API Endpoint.
3. Backend validates JSON -> Stores in Database -> Updates Likelihood Score.
4. Web Client queries Backend to display high-probability matches.

Development Workflow

Direct pushes to main are blocked.

1. Pull Latest: Always git pull origin main before starting.
2. Branch: Create a feature branch: git checkout -b feature/your-name-task.
3. Commit: Work in your folder (/ingestor, /backend, or /web-client).
4. Pull Request: Push your branch and open a PR on GitHub.
5. Review: Another team member must review your code before it can merge.