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#115 — Top 90.4%

v1shay

Vishay Agarwal

C

Getting there

Overall

0.0

/ 100

01 · Roasts

Serial Sprinter

12 repos, 0 stars, and a graveyard of 2-day wonder-projects: vox-agent died at 9 commits, archLLM-sim at 11, ml-forge at 25. You're great at starting things — finishing them is apparently someone else's problem.

CI? Never Heard of Her

Zero repos with CI out of 12. Not one. You've written LLM orchestrators, Blender agents, and multi-modal OS backends — but apparently a 10-line GitHub Actions YAML is the one engineering challenge that has defeated you.

The License Nihilist

Every single repo: 0 stars, 0 forks, no license. You're building in a legal grey zone for an audience of zero. At least archLLM-sim is consistent — no docs, no tests, no gitignore, maximum ambiguity.

README Roulette

vectra has design.md, ARCHITECTURE.md, STATUS.md, and docs/ — but no README. You wrote four documents to explain a project and skipped the one document GitHub actually shows people. Impressive commitment to being undiscoverable.

Hackathon Hero, Production Zero

echo-OS won a hackathon and has an 80 MB codebase with langgraph loops and multi-modal TTS. It also has 0 stars, 0 forks, no tests, no CI, and no type safety. The judges were impressed; the internet has no idea it exists.

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
    68C
  • Consistency
    20% weight
    65C
  • Quality
    20% weight
    72B
  • Depth
    15% weight
    65C
  • Breadth
    10% weight
    55D
  • Community
    10% weight
    25F

03 · Stats

365-day commit heatmap

85 active days

Less
More

Language distribution

6 langs
  • Python81%
  • PLpgSQL15%
  • Cython3%
  • C1%
  • TypeScript0%
  • C++0%

04 · Numbers

Owned repos

non-fork

15

Commits

last 12 months

616

Followers

4

Joined GitHub

Sep 2025

05 · Top repos

v1shay /

substack-network

60/100

SQL/Python Substack network crawler with typed language, structured architecture, tests, CI, comprehensive docs (docs/, ARCHITECTURE.md, design.md), and active 3-week development. Complex data pipeline for network analysis with comment enrichment and semantic embeddings.

I40Q75D65
READMETests
PLpgSQL01mo ago

v1shay /

vectra

48/100

Personal experimental project building a Blender AI assistant with agent reasoning, tool registry, and execution engine. Typed Python with comprehensive multi-file architecture, tests, and design docs (docs/ folder, design.md, ARCHITECTURE.md, STATUS.md), but no README, no CI, and no license.

I25Q65D55
Tests
Python01mo ago

v1shay /

echo-OS

48/100

Ambitious voice-first OS for accessibility (hackathon winner); functional agentic backend with langgraph loops, React frontend, and multi-modal STT/TTS integration; lacks tests, CI, and type safety in critical paths despite ~80 MB codebase.

I40Q55D50
README
Python02mo ago

v1shay /

sift

45/100

Early-stage TypeScript/Python full-stack app for semantic GitHub exploration via vector DB and LLM-powered search. Typed, documented, multi-layer architecture, but brand new (7 days old) with no users, stars, or external validation.

I25Q60D50
READMETyped
TypeScript01mo ago

v1shay /

frontend

42/100

Personal portfolio built with Next.js, React, TypeScript, Three.js shaders, and Tailwind CSS. Typed, structured multi-file layout with shader background effects. No README, tests, CI, or license; 22 of 30 recent commits in ~40 days indicates active but recent work. Demonstrates professional frontend craftsmanship but l

I25Q55D45
Typed
TypeScript01mo ago

v1shay /

neural-lens

40/100

Chrome extension + FastAPI backend for real-time in-context text analysis. Typed backend (Pydantic models), documented (docs/ folder, ARCHITECTURE.md, STATUS.md), modular structure, but nascent project with 0 stars and significant placeholder code.

I25Q50D45
README
JavaScript03mo ago

v1shay /

novaSTEM-frontend

38/100

TypeScript Next.js 14 nonprofit website frontend with React 18, Tailwind, and Framer Motion animations. Typed, structured multi-file layout (app/, components/, store/), but lacks README, tests, CI, license, and documentation.

I25Q50D35
Typed
TypeScript01mo ago

v1shay /

ml-forge

38/100

Early-stage ML orchestration pipeline with typed Python architecture for data ingestion, profiling, strategy inference, and model training. Recently created with active commits but minimal documentation and no CI/license yet.

I20Q45D50
READMETests
Python03mo ago

v1shay /

upliftArt-frontend

37/100

Early-stage TypeScript+React+Vite foundation website with polished 3D animations, shader backgrounds, and responsive design. No tests/CI; thin output but typed and structured, created within weeks.

I25Q50D35
READMETyped
TypeScript02mo ago

v1shay /

taquizas-chapala-web

35/100

Freelance catering website built in React/TSX with 30 commits over ~16 days. No README, tests, CI, or license; minimal public adoption signals (0 stars/forks). Typed language and structured multi-file layout (6.3 MB codebase) suggest professional work but lack of documentation and test infrastructure limits quality ass

I25Q35D45
Typed
CSS03mo ago

v1shay /

vox-agent

28/100

Fresh hardware-integrated speech-to-LLM project (2 days old, 9 commits) with structured Python modules (stream.py, transcribe.py, llm.py, run_live.py), typed code, and clear README. No tests, CI, or license; architectural scope suggests ~500 LOC suggesting one-sprint depth.

I15Q50D20
README
Python03mo ago

v1shay /

archLLM-sim

12/100

Bare-bones C++ simulation project with zero ecosystem presence, no documentation, no tests, and minimal file structure. Created 2 days ago with 11 commits—a short sprint with no supporting artifacts for reproducibility or understanding.

I5Q10D20
C++03mo ago

06 · Timeline

  1. Sep 23, 2025
    Joined GitHub
  2. Jan 26, 2026
    Created neural-lens — Real-time in-context data analysis from on-page user selections using a Manifest V3, FastAPI backend, and modular analysis pipeline
  3. Feb 9, 2026
    Created taquizas-chapala-web — Freelance development project for local catering service built in TSX, CSS, JavaScript, and React.js
  4. Feb 10, 2026
    Created ml-forge — Pipeline + sandbox for data ingestion, AI-powered feature engineering and regression, model development/testing, and graphs/research paper generation
  5. Feb 21, 2026
    Created vox-agent — Hardware-integrated Python agent, taking AirPods CoreAudio input and using speech recognition to deliver LLM-powered insight
  6. Feb 23, 2026
    Created archLLM-sim — C++ simulation optimizing LLM memory architectures that improves budget adherence by 95% and reduces HBM pressure by 30% via hardware-level token constraints
  7. Feb 28, 2026
    Created echo-OS — Voice-first OS for blind users enabling full hands-free computer control via natural language; winner of ElevenLabs-backed hackathon
  8. Mar 16, 2026
    Created frontend — Personal website built with TSX, React, Next.js, Three.js, shaders, Tailwind CSS
  9. Mar 22, 2026
    Created novaSTEM-frontend — NovaSTEM nonprofit website showcasing programs, impact, and student outreach, built with Next.js 14, React 18, and Tailwind CSS
  10. Mar 26, 2026
    Created substack-network — A large-scale Substack network modeling system, developed through research at Chapman, integrating graph construction on a SQL-centric architecture
  11. Mar 26, 2026
    Created vectra
  12. Mar 26, 2026
    Created upliftArt-frontend — Uplift Art foundation website showcasing mission, impact, and card galleries, built with React 18, GLSL, and Vite
  13. Apr 18, 2026
    Created sift — A vectorized representation of GitHub. Query in natural language, let AI sift and surface the perfect repo for you. Ship your next PR in minutes
  14. Apr 25, 2026
    Most recent push to sift

07 · Compare

github.com/
v1shay · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total62.1
Top-end curve+5.3
Final overall67.4

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.
v1shay · 67.4/100 — Rate My GitHub