01 · Roasts
93% HTML, Demographer by Day
Your language breakdown reads like a Quarto render log accidentally committed to GitHub. 93% HTML because everything you touch gets knitted into a webpage — R is your soul language but barely registers at 4%.
52% Stale Repo Graveyard
Over half your 70 repos haven't been touched in 2+ years. That's not a portfolio, that's an archaeological dig site. Future Ilya will keep inheriting Future Past Ilya's abandoned experiments.
1 PR/Year, 25 Issues
You filed 25 issues across the ecosystem but submitted exactly 1 pull request in the last year. You're an excellent bug reporter and a reluctant bug fixer on other people's code.
No CI. Ever. In Any Repo.
12 repos assessed. CI count: 0. Test count: 0. Your entire quality assurance strategy is 'it rendered without errors in my RStudio session.' Reproducibility researcher, heal thyself.
Sprint Archaeologist
graupel (1 commit), linuxcolors (1 day), laliga-preview (1 day), ai-tune (4 commits in 2 days) — you have a beautiful talent for creating repos, naming them, and never returning. At least the READMEs are there.
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
- Impact25% weight68C
- Consistency20% weight65C
- Quality20% weight62C
- Depth15% weight65C
- Breadth10% weight55D
- Community10% weight55D
03 · Stats
365-day commit heatmap
66 active days
Language distribution
- HTML93%
- R4%
- JavaScript2%
- CSS0%
- TeX0%
- SCSS0%
- Other1%
04 · Numbers
Owned repos
non-fork
60
Commits
last 12 months
140
Followers
291
Joined GitHub
Dec 2014
05 · Top repos
ikashnitsky /
ikashnitsky.github.io
Personal data journalism / teaching portfolio website built with Quarto. Demonstrates sustained work on R data visualization education and demographic research communication through 112 MB of structured blog content, custom theming, and interactive documentation.
ikashnitsky /
30daychart2026
Active dataviz portfolio project: 19 complete daily chart submissions across R/D3, well-documented system prompt, structured src/ layout, typed language (R), and meaningful git activity. Demonstrates sustained effort in data visualization education.
ikashnitsky /
dataviz-one
One-day R dataviz workshop with curated teaching materials, Quarto slides, and practical ggplot2 examples covering themes, colors, animation, and visualization principles for demographic data.
ikashnitsky /
us-names-app
R Shiny app visualizing median age of US names by popularity. Well-scoped data visualization project with structured build pipeline, typed R code, and external data attribution, but minimal documentation and no tests or CI.
ikashnitsky /
linuxcolors
Brand-new R color palette package (3 stars, <1 day old) offering Linux distro-themed ggplot2 scales. Typed R with README, ggplot2 integration, and structured src/ layout, but lacks tests, CI, and real-world adoption signals.
ikashnitsky /
r-pkg-whitelist
Personal R package reference list with curated tables, HTML documentation, and CSV export script. Minimal commits (2 of 30 days), zero stars/forks, but well-documented for its scope.
ikashnitsky /
4Rum
Internal organization repository documenting monthly R forum meetings at Statistics Denmark (DST). Minimal public scope: no stars, no forks, thin README listing 7 meeting topics with dates.
ikashnitsky /
x
Personal website static file repository with minimal adoption impact (0 stars/forks). Organized asset collection with basic hygiene (license, gitignore) but thin documentation. Shows sustained maintenance over 1+ years with recent commits, indicating owner actively manages site.
ikashnitsky /
dem-digest
Russian-language demographic research digest published as a regular column; 71MB codebase with 9-year history and recent activity, but minimal documentation and no discernible code structure in sampled files.
ikashnitsky /
ai-tune
Early-stage personal project collecting AI tuning scripts and guides. 1.4 MB of unstructured R, HTML, and Quarto files with minimal coordination; no tests, CI, or clear architecture. Created 2 days ago with 4 recent commits.
ikashnitsky /
laliga-preview
Single-week exploratory analysis of La Liga pundit predictions using R. Well-documented project with 31 KB codebase, clear visualization output, but minimal commit history (4 of 30 in recent window) and no tests or CI.
ikashnitsky /
graupel
Barely-initialized repository with 3KB codebase, single commit, no source files sampled, minimal README. Appears to be a scaffold/placeholder for a raindrop.io semantic search tool.
06 · Timeline
- Dec 22, 2014Joined GitHub
- Feb 6, 2017Created dem-digest — Demographic Digest is a regular column at Demoscope Weekly which publishes (in Russian) brief summaries of fresh demographic papers from the best academic journals.
- Dec 9, 2019Created us-names-app — Shyny app to visualize medial age of living people by name
- Dec 18, 2022Created x — static files for my personal website
- Dec 18, 2022Created ikashnitsky.github.io — Dr. Ilya Kashnitsky is a Senior Researcher @ Statistics Denmark
- Apr 8, 2025Created dataviz-one — One day dataviz workshop
- May 30, 2025Created 4Rum — R forum at DST organization materials
- Mar 20, 2026Created laliga-preview — Analysis of football game predictions from three pundits airing at a Russian YouTube channel https://youtube.com/playlist?list=PLZgJT1M3SJ9XVvZFlcJeCKUMzrMYCrCwc&si=RVs-ryd-bKHXuOB
- Apr 1, 2026Created 30daychart2026 — #30DayChartChallenge 2026 edition -- https://github.com/30DayChartChallenge/Edition2026
- Apr 4, 2026Created ai-tune — Tune up everything ai
- Apr 12, 2026Created linuxcolors — R package with color palettes sourced from the identity colors of the most popular Linux distros
- Apr 18, 2026Created r-pkg-whitelist — Selection of main R packages that need to be installed on my machine for comfortable work
- Apr 24, 2026Created graupel — fully local semantic search for raindrop.io library
- Apr 29, 2026Most recent push to ikashnitsky.github.io
07 · Compare
08 · Rubric
How this score was produced
Overall = Σ (category × weight) + gentle top-end curve
Tier thresholds
▸ How the pipeline works
- 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.
- 02Triage.A small model reads every repo's file tree + README and picks the 20 files per repo that actually reveal how you code.
- 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.
- 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.
- 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.