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#206 — Top 82.8%

ShyamSundhar1411

Shyam Sundhar

C

Getting there

Overall

0.0

/ 100

01 · Roasts

95% Jupyter, 0% Tests

Your language breakdown is 95% Jupyter Notebook and your test coverage is 0% across 9 of 10 repos. You've essentially built a very elaborate scratch pad and called it a portfolio.

soloPct: 100%

Every single repo is a solo project. You have 148 followers and totalPRsYear = 0. People are watching you commit to yourself in silence.

The 6-Year ANN

Your ANN repo spans 6 years and 25 commits. That's one commit every ~88 days. At this velocity, you'll finish a neural network sometime around 2041.

3-Day Project, Empty README

My-Agent-Lab was created and abandoned in 3 days with a README that literally says 'This project has no architecture selected.' Bold documentation strategy.

148 Followers, 0 PRs

You've somehow accumulated 148 followers without opening a single external PR or issue this year. They're following a ghost — a very productive, self-contained ghost.

Built using

Zoral

Shadows one worker for a week, then takes over their job with zero extra setup. Behaves exactly like the original.

zoral.ai

02 · Category breakdown

  • Impact
    25% weight
    56D
  • Consistency
    20% weight
    65C
  • Quality
    20% weight
    57D
  • Depth
    15% weight
    58D
  • Breadth
    10% weight
    55D
  • Community
    10% weight
    50D

03 · Stats

365-day commit heatmap

346 active days

Less
More

Language distribution

7 langs
  • Jupyter Notebook95%
  • Python1%
  • HTML1%
  • CSS1%
  • Java1%
  • JavaScript0%
  • Other1%

04 · Numbers

Owned repos

non-fork

90

Commits

last 12 months

465

Followers

148

Joined GitHub

May 2020

05 · Top repos

ShyamSundhar1411 /

Key-Hive-Kotlin

46/100

KeyHive is a local password manager mobile app in Kotlin with structured architecture (DI, repository pattern, paging), encryption utilities, and CSV import/export. No tests, no license, but typed + documented + CI configured for linting.

I25Q58D55
READMECITyped
Kotlin02mo ago

ShyamSundhar1411 /

structura-py

45/100

Structura is a Python CLI scaffolding tool with typed models (Pydantic), CI/lint automation, and multi-architecture support (MVC/MVCS/Hexagonal), but lacks unit tests and has minimal adoption (1 star). Quality is grounded in types, docs, and structured code; depth shown by multi-month activity with evolving features.

I25Q60D50
READMECI
Python11mo ago

ShyamSundhar1411 /

Zenri-Express-Backend

42/100

Personal Express+TypeScript backend API for a life companion app with Prisma ORM, Supabase auth, and typed request validation. No README or CI/tests, but clean typed architecture with proper service-repository pattern and ~10k LOC scope.

I25Q50D45
Typed
TypeScript02mo ago

ShyamSundhar1411 /

My-Go-Playground

40/100

Personal learning playground implementing 6+ rate-limiting algorithms and concurrency patterns in Go with tests and clear module structure, but no CI and zero adoption signals.

I25Q60D35
READMETestsTyped
Go02mo ago

ShyamSundhar1411 /

Visionify-Backend

38/100

Educational FastAPI backend for image classification (MNIST/CIFAR-10) with clean architecture and DI patterns. Untyped Python, no tests, pre-commit configured. Early-stage project with 0 stars/forks suitable for learning but lacks production maturity.

I25Q45D45
READMECI
Python01mo ago

ShyamSundhar1411 /

My-ML-Notebooks

33/100

Collection of ML learning notebooks (Jupyter + Python scripts) covering GPT implementation, computer vision, NLP, and LangGraph agents; typed Python code with structured modules but minimal documentation and no tests/CI.

I25Q40D35
README
Jupyter Notebook41mo ago

ShyamSundhar1411 /

Zenri-Frontend

33/100

Young Next.js 15 + TypeScript frontend (883 KB) with 30 commits over ~3.5 months. Typed, has README, but minimal project-specific docs, no tests/CI, and appears to be a personal learning/experimental project with 0 stars/forks.

I25Q40D35
READMETyped
TypeScript03mo ago

ShyamSundhar1411 /

My-Agent-Lab

23/100

Personal experimental FastAPI project for LangGraph-based agent systems with RAG/knowledge graph integration. Very early stage (3 days old, 6 commits), minimal documentation, no tests/CI, and no production-ready patterns.

I15Q35D20
README
Python03mo ago

ShyamSundhar1411 /

ANN

18/100

Early-stage personal neural network learning project in Jupyter Notebooks with no documentation, tests, CI, or license. 25 commits over ~6 years suggests occasional tinkering rather than sustained development.

I10Q15D30
Jupyter Notebook04mo ago

ShyamSundhar1411 /

Unifyd-React-Native

15/100

Boilerplate Expo React Native starter project with zero commits in past month, no tests/CI, and generic scaffold README. Recently created (Jan 24, 2026) with minimal substantive code.

I15Q25D5
READMETyped
TypeScript04mo ago

06 · Timeline

  1. May 13, 2020
    Joined GitHub
  2. Jun 15, 2020
    Created ANN — My first Neural Network
  3. Jul 29, 2022
    Created My-ML-Notebooks — Collection of Jupyter notebooks showcasing machine learning practices, including computer vision, NLP, classical ML algorithms, and paper replications.
  4. Oct 6, 2024
    Created Visionify-Backend — 🧠 Visionify is an interactive image classification platform. 🚀 This is its backend API built with FastAPI, clean architecture, and DI—supporting MNIST, Fashion MNIST, and CIFAR-1
  5. Dec 11, 2024
    Created Key-Hive-Kotlin — KeyHive is a cloud-free password manager designed to help you securely store, manage, and organize your passwords locally on your device
  6. Mar 7, 2025
    Created structura-py — Structura is a CLI tool that automates folder structure generation and dependency management for Python projects. It supports multiple architectures (MVC, MVCS, Hexagonal) and fram
  7. Sep 22, 2025
    Created Zenri-Express-Backend — Zenri Express Backend is an Express + TypeScript API server for Zenri, a personal life companion app. It provides type-safe database access with Prisma, request validation with Zod
  8. Nov 4, 2025
    Created Zenri-Frontend — Zenri Frontend - A modern Next.js 15 + TypeScript app for Zenri, a personal life companion platform. Built with shadcn/ui, Tailwind CSS, Zustand, and React Query, it features type-
  9. Jan 15, 2026
    Created My-Go-Playground — Hands-on implementations of core systems fundamentals and patterns in Go, built from first principles.
  10. Jan 24, 2026
    Created Unifyd-React-Native
  11. Feb 16, 2026
    Created My-Agent-Lab
  12. Apr 24, 2026
    Most recent push to Visionify-Backend

07 · Compare

github.com/
ShyamSundhar1411 · 6dmedian coder

08 · Rubric

How this score was produced

Overall = Σ (category × weight) + gentle top-end curve

CategoryWeightScoreContrib.
Raw total57.6
Top-end curve+4.4
Final overall62.0

Tier thresholds

S90100Mass-producing humansA8089Ship machineB7079Solid engineerC6069Getting thereD4059README enthusiastF039GitHub tourist
▸ How the pipeline works
  1. 01Scrape.Pull every non-fork repo pushed in the last 90 days, plus your contribution calendar, followers, and language byte counts — straight from GitHub's REST & GraphQL APIs.
  2. 02Triage.A small model reads every repo's file tree + README and picks the 20 files per repo that actually reveal how you code.
  3. 03Grade each repo. All repos run in parallel through a fast scoring model that reads the picked files and rates each one independently on Impact, Quality, and Depth — with evidence citations.
  4. 04Aggregate. A larger reasoning model combines the per-repo scores with server-computed stats (heatmap, commit cadence, language entropy, follower count) to produce the 6-dimension profile score + roasts.
  5. 05Correct.Deterministic server-side checks enforce anchor-scale floors (e.g. a profile with 2,000+ public commits can't score 30 Consistency) and recompute the final verdict.

~90 seconds per profile, ~$0.25 in compute. Total of ~240 files read across your top-12 repos. One rating per GitHub account per day.

▸ Data sources & caveats
  • Heatmap & commit totals: GitHub GraphQL contributionsCollection — covers the last 365 days, includes private repos when the user has opted in (default).
  • Language %: byte totals across the top 30 owned non-fork repos.
  • Curve: a small upward nudge centered on raw score ≈ 70, capping at 100. Prevents specialists from being unfairly penalised for narrow breadth.
  • Anchor corrections: when server-measured signals (e.g. privateWorkLikely, multiRepoVolume, follower count) mandate a minimum category score, the aggregation step enforces it. These are signal-conditional, not identity-based floors.
ShyamSundhar1411 · 62.0/100 — Rate My GitHub