Case study / AI-powered developer analysis suite
EggScan
A Spring Boot and React system for profile scanning, developer comparison, repository deep dives, commit analysis, README evaluation, and stack analysis.
Analysis chamber / EggScan
Raw GitHub data.
Readable evidence.
The suite changes lenses without changing the evidence boundary.
Mode 01 / 06Profile
- Input
- Profile + contributions
- Output
- Readable scoring and feedback
GitHub GraphQL→Spring Boot→Groq analysis→Human-readable verdict
Overview
What the system is
EggScan has grown beyond a profile scorer into a developer-analysis suite with multiple reviewer personas and focused tools for profiles, repositories, commits, READMEs, and technology stacks.
Problem
The constraint that shaped it
Turn raw GitHub data into readable portfolio and repository feedback without hiding the technical evidence.
Contribution
What I owned
- Backend API and GitHub integration
- AI analysis flows
- Frontend experience and feature expansion
Capabilities
What it does
- 01Profile scanAnalyzes GitHub profile and contribution data with readable scoring and feedback.
- 02Developer battleCompares two developer profiles through the same evidence-driven flow.
- 03Repository deep diveExamines a repository beyond top-level profile signals.
- 04Focused analysisIncludes commit-message, README, and stack evaluation modes.
- 05Reviewer personasOffers multiple presentation styles for the analysis.
Engineering
Decisions on record
- Data
- GitHub GraphQL consolidates profile and repository evidence.
- Backend
- Spring Boot owns integration and analysis orchestration.
- AI boundary
- Model output is analysis, not verified fact about a developer.
Evidence boundary
Known limitations
- Live provider behavior requires runtime verification; automated checks alone do not prove production reliability