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#162 — Top 88.7%

Sohan-Suchdev

Sohan Suchdev

C

Getting there

Overall

0.0

/ 100

01 · Roasts

Commit Vampire

374 commits in a year but the heatmap looks like a horror film: months of flat-lining, then a frantic week-long binge. Your coding schedule has more plot twists than a thriller novel.

License Phobia

Seven projects, zero licenses. Congratulations — every repo you own is legally radioactive. If someone forks zsh-ai-copilot, you literally cannot stop them from selling it at a market stall.

Solo Operator

soloPct = 100%. Not a single PR merged, not a single collaborator, 0 following. You're not building in public — you're building in a sealed bunker. Even leetcode bots have more social presence.

Problem Dump Enthusiast

Two separate repos (leetcode + neetcode-submissions) for dumping algorithm solutions. One has CI, one doesn't. Neither has tests. You've automated the upload of code you haven't tested. Peak efficiency.

Star-Follower Ratio Tragedy

17 total stars across 15 repos and 2 followers, yet you follow 0 people. The GitHub social graph for your account is literally a single node with no edges. Network centrality: undefined.

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
    75B
  • Depth
    15% weight
    58D
  • Breadth
    10% weight
    80A
  • Community
    10% weight
    25F

03 · Stats

365-day commit heatmap

45 active days

Less
More

Language distribution

7 langs
  • Jupyter Notebook31%
  • TypeScript29%
  • Python25%
  • C++6%
  • JavaScript4%
  • Kotlin2%
  • Other3%

04 · Numbers

Owned repos

non-fork

15

Commits

last 12 months

374

Followers

2

Joined GitHub

Jul 2025

05 · Top repos

Sohan-Suchdev /

4d-minesweeper

58/100

Well-architected 4D Minesweeper portfolio project with Kotlin/Spring backend, Vanilla JS frontend, strong security (sanitized DTOs), and performance optimization. Typed, documented, CI-enabled, but minimal stars/adoption; architectural scope and craft place it solidly in the "active portfolio" band.

I40Q78D55
READMECITyped
Kotlin116d ago

Sohan-Suchdev /

cpp-raytracer

51/100

Educational C++20 ray tracer following Peter Shirley's trilogy with complete Monte Carlo integration, lock-free multithreading, and comprehensive test suite (Catch2 covering Vec3, intersections, materials, BVH, PDFs).

I25Q72D55
READMETestsCI
C++12mo ago

Sohan-Suchdev /

Imperial_Predict

45/100

ImperialPredict is a working grade-tracking tool for Imperial College students built with Next.js, Supabase, TypeScript, and Recharts. Typed, documented, and structured multi-file layout, but minimal adoption, no tests/CI, and no license.

I25Q60D50
READMETyped
TypeScript227d ago

Sohan-Suchdev /

avellaneda-stoikov-py

42/100

Educational market-making simulator implementing Avellaneda-Stoikov stochastic control with multiple baseline strategies. Well-structured, documented, and runnable, but early-stage with minimal adoption (1 star, no external users).

I25Q60D40
READMECI
Python11mo ago

Sohan-Suchdev /

zsh-ai-copilot

41/100

Terminal AI agent converting natural language to bash commands via FastAPI daemon + LangGraph + ChromaDB. Typed Python with comprehensive architecture, strong test suite, and CI/CD—but minimal adoption (8 stars, brand new, no license, single developer).

I25Q62D38
READMETestsCI
Python82mo ago

Sohan-Suchdev /

leetcode

25/100

LeetCode solutions collection with solid algorithm implementations (LFU cache, binary trees, heaps) across Python/C++, automated CI sync, but no README, docs, tests, or project structure—pure problem dump.

I15Q25D35
CI
Python014d ago

Sohan-Suchdev /

neetcode-submissions

20/100

Personal NeetCode submission sync repo created 8 days ago with 30 commits. Auto-generated solutions folder (no actual code sampled), minimal documentation explaining the sync mechanism, no tests or CI, 39KB size suggests minimal content.

I15Q25D20
README
Python03mo ago

Sohan-Suchdev /

Sohan-Suchdev

18/100

Personal portfolio README showcasing interests in quant and ML; no actual project code sampled. 19 KB, 1 star, minimal commits. Early-stage or placeholder repo.

I15Q25D15
README
Unknown12mo ago

06 · Timeline

  1. Jul 2, 2025
    Joined GitHub
  2. Nov 27, 2025
    Created Imperial_Predict — ImperialPredict is a grade calculator for Imperial College students. It lets you input marks for coursework and exams to calculate your weighted module scores and overall year aver
  3. Nov 27, 2025
    Created Sohan-Suchdev
  4. Dec 1, 2025
    Created avellaneda-stoikov-py — A stochastic optimal control simulation implementing the Avellaneda-Stoikov model to optimise market-making spreads and neutralise inventory risk.
  5. May 19, 2026
    Created neetcode-submissions — My NeetCode.io problem submissions
  6. May 19, 2026
    Created leetcode
  7. Jun 9, 2026
    Created zsh-ai-copilot — A terminal-native AI agent that converts natural language into validated, environment-aware shell commands. Powered by a persistent local FastAPI daemon, LangGraph, and ChromaDB fo
  8. Jun 9, 2026
    Created cpp-raytracer — A lock-free, multi-threaded CPU path tracer built from scratch in C++20. Features a contiguous frame buffer and a complete Monte Carlo integration framework with explicit light imp
  9. Jun 9, 2026
    Created 4d-minesweeper — A 4D Minesweeper web game engineered for strict architectural security and performance. Pairs a secure Kotlin/Spring Boot backend with a highly optimised, framework-free Vanilla JS
  10. Aug 18, 2026
    Most recent push to leetcode

07 · Compare

github.com/
Sohan-Suchdev · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total61.2
Top-end curve+5.1
Final overall66.3

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.
Sohan-Suchdev · 66.3/100 — Rate My GitHub