▸ This tool was built by an AI agent from Zoral
← RATE MY GITHUB

#65 — Top 94.6%

JosephBARBIERDARNAL

Joseph Barbier

B

Solid engineer

Overall

0.0

/ 100

01 · Roasts

Jupyter Monolith

64% of your codebase is Jupyter Notebooks and 36% is HTML — that's 100% of your bytes accounted for, leaving Python, Rust, R, and JS rounding to literal 0%. Your language chart is a pie with two enormous slices and five invisible crumbs.

Serial Sprinter

red-flip: built in 2 days. parseplot: 1 commit. monstre: 3 commits, blank README. pyshare: 12 commits, 2 days old. You have 2,220 commits this year but somehow most repos look like they were born on a Friday afternoon and abandoned by Sunday brunch.

Test Desert

10 repos scored. HAS_TESTS=yes: exactly zero. You've got CI pipelines, architectural docs, design.md files, and pre-commit hooks — but not a single test suite committed. The scaffolding for quality is there; the quality itself ghosted.

The License Phantom

Across 52 public repos, licenses are conspicuously absent from the majority of scored projects. You're shipping Rust game servers, Python libraries, and chart parsers into the void with no legal clarity. Open source without a license is just public code that nobody can legally use.

monstre

1 KB. Blank README. 3 commits. Created and last pushed the same day. 'monstre' is the most accurate name for a repo that exists purely to haunt your contributions grid.

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
    88A
  • Quality
    20% weight
    57D
  • Depth
    15% weight
    65C
  • Breadth
    10% weight
    65C
  • Community
    10% weight
    65C

03 · Stats

365-day commit heatmap

299 active days

Less
More

Language distribution

6 langs
  • Jupyter Notebook64%
  • HTML36%
  • Python0%
  • JavaScript0%
  • TeX0%
  • R0%

04 · Numbers

Owned repos

non-fork

29

Commits

last 12 months

2,220

Followers

203

Joined GitHub

Feb 2021

05 · Top repos

JosephBARBIERDARNAL /

barbierjoseph.com

47/100

Personal homepage project with 27 MB codebase and CI/CD pipeline. Documented via design.md, ARCHITECTURE.md, STATUS.md; sustained over ~2 years with 30 recent commits, but minimal external impact (1 star, no forks).

I25Q50D65
CI
HTML12mo ago

JosephBARBIERDARNAL /

pyshare

40/100

Early-stage Python library for reading SHARE epidemiological survey data. Typed, documented with design.md and docs/, CI setup (ruff, type checking), but nascent (0 stars, 1 day old, 12 commits, no tests, no license).

I25Q60D35
READMECI
Python01mo ago

JosephBARBIERDARNAL /

red-flip

40/100

Real-time multiplayer Rock-Paper-Scissors game with Elo ranking, actor-based matchmaking, and WebSocket gameplay. Early-stage project (2 days old) with solid Rust architecture but no test coverage, minimal docs, and zero production adoption.

I25Q60D35
READMECITyped
Rust03mo ago

JosephBARBIERDARNAL /

tidytuesday

40/100

Personal data visualization portfolio showcasing TidyTuesday entries and custom analyses. Features polars/matplotlib pipelines, reproducible uv setup, and clean visual outputs but lacks tests, CI, license, and architectural documentation.

I25Q50D45
README
Python104mo ago

JosephBARBIERDARNAL /

talk

35/100

Archive of personal conference talk materials (slides + videos) spanning Typst, R visualization, and Python packaging. No source code, untyped HTML/assets, 30 commits over ~8 months.

I15Q35D55
README
HTML01mo ago

JosephBARBIERDARNAL /

static

33/100

37MB codebase with 30 commits over ~20 months, but minimal documentation (README is empty), no tests, no CI, and unknown language. Substantial file size suggests meaningful scope, but lack of typed language and testing infrastructure limits quality assessment.

I25Q30D45
README
Unknown02mo ago

JosephBARBIERDARNAL /

playing-with-rust

33/100

Educational Rust learning exercises with 10 structured lessons covering ownership to lifetimes. Has README, typed Rust code, and organized module structure, but no tests passing, no CI/CD, and minimal original contribution—primarily pedagogical scaffolding.

I15Q50D35
READMETyped
Rust03mo ago

JosephBARBIERDARNAL /

30DayChartChallenge

23/100

A personal 30-day chart challenge portfolio showcasing 5 data visualizations built with Python matplotlib and interactive HTML; minimal scope (9 commits in 3 days), no tests/CI, untyped Python with basic documentation.

I15Q35D20
README
HTML02mo ago

JosephBARBIERDARNAL /

parseplot

20/100

Experimental Rust/Python matplotlib chart parser using pyo3. Single-commit 683 KB prototype with minimal features, no tests, lacks license, and shows no sustained development history.

I15Q40D5
READMECITyped
Rust01mo ago

JosephBARBIERDARNAL /

monstre

5/100

Empty scaffold project created April 4, 2026 with only 1 KB size, 3 commits, blank README titled 'monstre', and no substantive code, tests, CI, or documentation.

I5Q10D5
README
HTML02mo ago

06 · Timeline

  1. Feb 27, 2021
    Joined GitHub
  2. Jun 21, 2024
    Created barbierjoseph.com — My homepage
  3. Aug 15, 2024
    Created static
  4. Mar 4, 2025
    Created tidytuesday — My contributions to the TidyTuesday challenge, among other visualizations
  5. Aug 13, 2025
    Created talk — The material and video of my talks
  6. Jan 23, 2026
    Created playing-with-rust — trying to learn rust
  7. Feb 12, 2026
    Created red-flip
  8. Mar 28, 2026
    Created 30DayChartChallenge — My charts for the 30DayChartChallenge edition 2026
  9. Apr 4, 2026
    Created monstre
  10. Apr 21, 2026
    Created parseplot — Experimental parsing of matplotlib charts, in Rust
  11. Apr 23, 2026
    Created pyshare — Python interface to work with SHARE data (Survey of Health, Ageing and Retirement in Europe)
  12. Apr 24, 2026
    Most recent push to pyshare

07 · Compare

github.com/
JosephBARBIERDARNAL · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total65.8
Top-end curve+5.8
Final overall71.5

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.
JosephBARBIERDARNAL · 71.5/100 — Rate My GitHub