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#171 — Top 88.1%

blancusjh

Jhonatan S Blanco

C

Getting there

Overall

0.0

/ 100

01 · Roasts

The CI Boycott

10 repos, 232 tests in geometrical-raytracer alone, 69 in Diffractor — and not a single GitHub Actions workflow file across the entire portfolio. You've built a validation cathedral with no automatic alarm system.

Nine-Minute Masterpiece

cartesian-surfaces-stl-generator: Newton-Raphson solver, surface-of-revolution mesh, STL export, and 5 modules — all committed between 02:35:12 and 02:41:39. Either you pre-wrote it elsewhere or you type at 780 LOC/minute.

Stars: 2. Modules: Infinite.

You have ARCHITECTURE.md, STATUS.md, design.md, and PLAN.md in multiple repos, rigorous BEM reference validation pipelines, and exactly 2 total GitHub stars — both from yourself, presumably.

The License Anarchist

Diffractor, wavec, fractals, cartesian-surfaces-stl-generator — gorgeous optics code released into a legal grey zone. No license means nobody can legally use it, which at 0 forks is technically fine.

Heatmap Archaeologist

40 of 52 heatmap weeks are completely empty, then week 47 onward looks like a physics department deadline hit. Your commit history reads like an ECG with a very late heartbeat.

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
    62C
  • Consistency
    20% weight
    65C
  • Quality
    20% weight
    72B
  • Depth
    15% weight
    60C
  • Breadth
    10% weight
    65C
  • Community
    10% weight
    25F

03 · Stats

365-day commit heatmap

65 active days

Less
More

Language distribution

6 langs
  • Jupyter Notebook43%
  • HTML29%
  • Lua14%
  • C++7%
  • Python7%
  • TeX1%

04 · Numbers

Owned repos

non-fork

10

Commits

last 12 months

339

Followers

0

Joined GitHub

Jan 2026

05 · Top repos

blancusjh /

geometrical-raytracer

62/100

Advanced optical ray-tracing toolkit in Jupyter Notebook format with 12,000 LOC across 9 packages, vectorized numpy propagation, Cartesian stigmatic surfaces, full test suite (232 tests), and design.md + ARCHITECTURE.md documentation. Production-ready research code.

I25Q75D60
READMETests
Jupyter Notebook01mo ago

blancusjh /

vecdiff

50/100

Specialized Python package for vector diffraction field propagation with structured architecture, comprehensive documentation, and extensive examples. Limited adoption (1 star, no external followers) but scientifically rigorous and well-engineered.

I40Q60D50
READMETests
Python116d ago

blancusjh /

Diffractor

48/100

Typed Python optics library with rigorous validation architecture and geometric exactness, but narrow adoption (1 star, personal project exploring scalar Helmholtz wave diffraction with dual-package monorepo, minimal external footprint).

I25Q70D50
READMETests
Jupyter Notebook112d ago

blancusjh /

wavec

42/100

Specialized physics package for vector wave optics on curved interfaces. Well-structured with typed code, comprehensive tests (33 physics tests in tests/), and rigorous mathematical foundation, but nascent (v0.2, 3 commits, created 2 days ago). Clear scientific value for optics research but no external adoption signals

I25Q60D35
READMETests
Jupyter Notebook024d ago

blancusjh /

thesis-about-vectorial-diffraction

38/100

Undergraduate thesis repository in Lua/LaTeX with structured chapters, appendices, and figure management. Well-organized with build tooling but limited scope as an academic document project with zero external adoption signals.

I15Q45D50
README
Lua01mo ago

blancusjh /

toc-generator

32/100

A personal Python tool for extracting table of contents from scanned PDFs using Gemini and PyMuPDF, shipped with minimal tests/CI but typed code and meaningful documentation. Created and pushed within 2 minutes on 2026-06-21, showing experimental single-push pattern.

I25Q50D20
README
Python02mo ago

blancusjh /

cfd-openfoam

28/100

Educational OpenFOAM case studies (heat equation, sphere convection, natural convection) with clear structure and README. No tests, CI, license, or typed language. 9MB codebase created 2 days ago with 20 commits.

I15Q45D20
README
C++01mo ago

blancusjh /

voley-dron

25/100

Competition submission scaffold for Skydio X2 ping-pong task with instruction.md, data/policy_spec.json, and basic test structure—no license, untyped Python, minimal sustained development (3 days old, 20 commits).

I15Q40D20
READMETests
Python01mo ago

blancusjh /

cartesian-surfaces-stl-generator

23/100

Experimental optical lens geometry generator using Cartesian ovoids. Untyped Python with clear README, structured modules, and working demos, but minimal commits and zero external adoption signals in a fresh repo.

I15Q50D5
READMETests
Python02mo ago

blancusjh /

fractals

20/100

Educational Mandelbrot fractal renderer comparing three Python approaches (NumPy, Numba, GPU/GLSL). Single-day project with minimal commits, untyped Python, no tests/CI, and acknowledged precision limitations but functional demonstrations.

I15Q40D5
README
Python02mo ago

06 · Timeline

  1. Jan 15, 2026
    Joined GitHub
  2. Mar 13, 2026
    Created Diffractor
  3. May 14, 2026
    Created thesis-about-vectorial-diffraction
  4. May 25, 2026
    Created vecdiff
  5. Jun 21, 2026
    Created toc-generator
  6. Jun 23, 2026
    Created cartesian-surfaces-stl-generator
  7. Jun 23, 2026
    Created fractals
  8. Jul 9, 2026
    Created geometrical-raytracer
  9. Jul 15, 2026
    Created voley-dron — Skydio X2 quadrotor ping-pong policy — MuJoCo, 4 gates + target box
  10. Jul 18, 2026
    Created cfd-openfoam
  11. Aug 8, 2026
    Created wavec
  12. Aug 20, 2026
    Most recent push to Diffractor

07 · Compare

github.com/
blancusjh · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total60.9
Top-end curve+5.1
Final overall66.0

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.
blancusjh · 66.0/100 — Rate My GitHub