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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.

CategoryAI-powered developer analysis suiteStatusDeployedRoleFull-stack developerContextPersonal projectStackSpring Boot · React · Groq · GitHub GraphQLLicenseMITLiveOpen build ↗SourceGitHub ↗

Analysis chamber / EggScan

Raw GitHub data.
Readable evidence.

The suite changes lenses without changing the evidence boundary.

REPOSITORY SIGNAL / MODE 01HUMAN REVIEW REQUIRED
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