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#409 — Top 65.8%

ParvTiwari

Parv Tiwari

D

README enthusiast

Overall

0.0

/ 100

01 · Roasts

Speed-Run Developer

Task-Manager: 4 commits in 5 minutes. File-Manager: created and done same day. Gold-Price-Prediction-Model: 2 commits in 85 seconds. You're not building software, you're doing time trials.

Secret Secret

MetroMart has 'metromart_secret_key' hardcoded directly in app.js. You built a supermarket management system with a loyalty points engine and 6 triggers — and then left the keys under the doormat.

README-Only Infrastructure

21 repos. 0 test suites. 0 CI pipelines. 0 licenses. The README flag is the only green light across your entire portfolio. You've mastered the art of documenting things that don't have tests.

Invisible to the Internet

0 followers, 5 total stars across 21 repos. Your portfolio site (Portfolio-PT) is built with GSAP animations and Nodemailer — but apparently nobody's received that email yet.

LSTM in 85 Seconds

Gold-Price-Prediction-Model: a full LSTM gold price predictor, committed start-to-finish in under two minutes. Either you're the fastest ML engineer alive or this is a copy-paste from a Kaggle notebook.

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
    48D
  • Consistency
    20% weight
    55D
  • Quality
    20% weight
    57D
  • Depth
    15% weight
    50D
  • Breadth
    10% weight
    65C
  • Community
    10% weight
    25F

03 · Stats

365-day commit heatmap

77 active days

Less
More

Language distribution

7 langs
  • Jupyter Notebook34%
  • JavaScript27%
  • EJS13%
  • Java9%
  • HTML6%
  • CSS5%
  • Other6%

04 · Numbers

Owned repos

non-fork

16

Commits

last 12 months

202

Followers

0

Joined GitHub

Jul 2023

05 · Top repos

ParvTiwari /

Portfolio-PT

41/100

Personal portfolio built with Next.js 16, React 19, GSAP animations, and Tailwind CSS. Features contact form with email automation via Nodemailer and scroll-triggered animations. Lacks tests, CI, and license but demonstrates structured components and modern web practices.

I25Q60D35
README
JavaScript11mo ago

ParvTiwari /

DocuSearch-AI

35/100

Personal RAG project built with Streamlit + Groq for document Q&A. Implements chunking and keyword-based retrieval without embeddings. Functional but lacks tests, CI, typing, and architectural documentation beyond README.

I25Q45D35
README
Python01mo ago

ParvTiwari /

MetroMart

35/100

Personal supermarket management system with Node/Express, Supabase, multi-table schema, but limited production signals—low stars (3), no tests, no CI, thin docs for non-DB code, hardcoded secrets.

I25Q45D40
README
EJS31mo ago

ParvTiwari /

NewsMind-AI

32/100

Personal AI news platform with backend+frontend full stack built in ~1 hour; demonstrates typed JS, structured architecture, and working integration with NewsAPI+Groq LLM, but ultra-fresh (created 2026-03-28, 1 commit in 30s), no users or production signals.

I25Q50D20
README
JavaScript02mo ago

ParvTiwari /

Shell

23/100

Educational Unix shell implementation in C with piping, redirection, and signal handling. Single-week effort (~4 commits in 6 minutes), 12 KB codebase, no tests/CI, demonstrable learning project with multiple OS concepts implemented.

I15Q35D20
README
C01mo ago

ParvTiwari /

Task-Manager

15/100

One-off educational C project demonstrating basic Linux process management via system calls, minimal scope (5 KB, single file), created and completed within 5 minutes on 2026-04-19.

I15Q25D5
README
C01mo ago

ParvTiwari /

File-Manager

15/100

Minimal educational C project demonstrating Unix file system calls. Single 500-line file with basic utilities (copy, merge, stat, cat, word count), no tests/CI, created and finished same day.

I15Q25D5
README
C01mo ago

ParvTiwari /

Gold-Price-Prediction-Model

15/100

Single Jupyter notebook for gold price prediction using LSTM with minimal documentation, no tests, no CI, and only 2 commits created within 2 minutes. Essentially a one-off tutorial/exploration piece.

I15Q25D5
README
Jupyter Notebook03mo ago

06 · Timeline

  1. Jul 10, 2023
    Joined GitHub
  2. Oct 9, 2025
    Created MetroMart
  3. Dec 30, 2025
    Created Portfolio-PT
  4. Feb 24, 2026
    Created Gold-Price-Prediction-Model
  5. Mar 5, 2026
    Created DocuSearch-AI
  6. Mar 28, 2026
    Created NewsMind-AI
  7. Apr 17, 2026
    Created Shell — This project is a lightweight implementation of a Unix-like command-line shell written in C. It supports core shell functionalities such as command execution, piping, input/output
  8. Apr 19, 2026
    Created File-Manager — A simple command-line File Manager built in C using low-level system calls. This project demonstrates core file handling operations in a Unix/Linux environment without relying on h
  9. Apr 19, 2026
    Created Task-Manager — A simple command-line based Task Manager implemented in C using Linux system calls. This project provides essential process management functionalities similar to basic system monit
  10. Apr 19, 2026
    Most recent push to Task-Manager

07 · Compare

github.com/
ParvTiwari · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total50.9
Top-end curve+2.8
Final overall53.7

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.
ParvTiwari · 53.7/100 — Rate My GitHub