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#150 — Top 91.4%

Sharveswar007

SHARVESWAR.M

C

Getting there

Overall

0.0

/ 100

01 · Roasts

Feature buffet, test famine

CareerPath, Candidate-Portal, and MoneyDa pack serious workflows, yet every scored repo reports no automated tests.

CI is a cameo

Only CareerPath and Type-plus show CI; 9 of 11 scored projects are shipping without an automated pipeline.

Portfolio beats popularity

58 public repos and 141 multi-repo recent commits, but only 5 total stars: the output is outrunning the audience.

The product factory is real

CareerPath, HIRENEX, MoneyDa, S-News-App, and YOLO/Arduino prove range—now turn a few into maintained, adopted flagships.

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
    65C
  • Depth
    15% weight
    58D
  • Breadth
    10% weight
    65C
  • Community
    10% weight
    55D

03 · Stats

365-day commit heatmap

59 active days

Less
More

Language distribution

7 langs
  • TypeScript56%
  • HTML16%
  • JavaScript13%
  • Python5%
  • CSS5%
  • PLpgSQL2%
  • Other3%

04 · Numbers

Owned repos

non-fork

55

Commits

last 12 months

332

Followers

14

Joined GitHub

Feb 2025

05 · Top repos

Sharveswar007 /

CareerPath

58/100

CareerPath is a substantial documented TypeScript/Next.js platform combining AI counseling, assessments, coding execution, resume OCR/ATS analysis, Supabase persistence, and student dashboards, but it has only 1 star and no demonstrated external adoption.

I25Q68D50
READMECITyped
TypeScript123d ago

Sharveswar007 /

Portfolio_Sharveswar

47/100

A substantial Astro/React portfolio with typed project data, static project and award routes, responsive motion-heavy UI, SEO metadata, and several live/demo links; adoption remains unproven at 0 stars and 0 forks.

I30Q60D50
READMETyped
TypeScript01mo ago

Sharveswar007 /

Candidate-Portal

45/100

A substantial typed Next.js recruitment platform with AI assessment, Supabase persistence, code execution, scoring, and proctoring workflows, but currently shows no public adoption and lacks tests, CI, and a license.

I25Q60D50
READMETyped
TypeScript02mo ago

Sharveswar007 /

HR-portal

45/100

A documented, typed Next.js/Supabase HR dashboard with analytics, candidate review, live proctoring, and PDF resume parsing; substantial feature scope is offset by zero adoption signals, absent tests/CI/license, and risky admin API patterns.

I22Q58D50
READMETyped
TypeScript02mo ago

Sharveswar007 /

MoneyDa

37/100

MoneyDa is a documented TypeScript/Next.js finance dashboard with CSV analytics, AI chat, receipt OCR, fraud tooling, simulation, and Razorpay links, but it has no visible adoption, tests, CI, or license.

I20Q55D35
READMETyped
TypeScript015d ago

Sharveswar007 /

Sisco-AI-Chatbot

35/100

A polished vanilla JavaScript Groq chatbot with local multi-session history and a Netlify serverless proxy, but no tests, CI, license, or demonstrated adoption.

I20Q38D45
README
JavaScript02mo ago

Sharveswar007 /

S-News-App

34/100

A small, documented Flask and vanilla JavaScript news app with category feeds, pagination, dark mode, and responsive card-based presentation, but no tests, CI, license, or typed implementation.

I20Q48D35
README
CSS02mo ago

Sharveswar007 /

Type-plus

31/100

A polished vanilla frontend typing dashboard with documented features and GitHub Pages deployment, but no tests, license, typed code, or demonstrated adoption.

I20Q38D35
READMECI
Python02mo ago

Sharveswar007 /

Sharveswar007

30/100

A polished GitHub profile README highlighting the author, featured repositories, and contact links, but with no source files, tests, CI, license, or demonstrated external adoption.

I25Q30D35
README
Unknown02mo ago

Sharveswar007 /

YOLO-Object-Detection

28/100

A documented YOLOv8/OpenCV demo that connects electronic-device detection to an Arduino LED, but with only 1 star, two sampled implementation files, and no tests, CI, license, or typed structure.

I20Q35D25
README
Python12mo ago

Sharveswar007 /

QR-image-generation-using-node-npm

25/100

A small Node.js CLI that prompts for a URL, writes a QR PNG and saves the URL text; it has a README and test script but minimal documentation and no substantive test suite.

I15Q40D20
READMETests
JavaScript02mo ago

06 · Timeline

  1. Feb 5, 2025
    Joined GitHub
  2. Mar 20, 2025
    Created YOLO-Object-Detection — Object detection using YOLOv8 with Arduino LED control
  3. Apr 26, 2025
    Created Sharveswar007
  4. May 6, 2025
    Created Type-plus — TypeAI-plus
  5. Jun 23, 2025
    Created QR-image-generation-using-node-npm
  6. Jul 9, 2025
    Created S-News-App — Hosted on Render
  7. Jul 9, 2025
    Created Sisco-AI-Chatbot — Site
  8. Dec 20, 2025
    Created CareerPath
  9. Feb 11, 2026
    Created HR-portal — HIRENEX - HR Portal
  10. Feb 11, 2026
    Created Candidate-Portal — HIRENEX - Candidate Portal
  11. Jun 28, 2026
    Created Portfolio_Sharveswar — Portfolio of Sharveswar Madasamy
  12. Aug 26, 2026
    Created MoneyDa
  13. Sep 5, 2026
    Most recent push to MoneyDa

07 · Compare

github.com/
Sharveswar007 · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total63.7
Top-end curve+5.5
Final overall69.2

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.
Sharveswar007 · 69.2/100 — Rate My GitHub