01 · Roasts
The Immortal Research Repo
xfertility was created in December 2021 and last pushed February 2026 — a 4-year lifespan with only 4 commits sampled from the last 30. That's not maintenance, that's haunting.
HTML Economist
78% of your codebase is HTML, yet your domain is demographic mortality research. Somewhere a D3.js chart is doing more epidemiology than the R code it's wrapped around.
License? Never Heard of Her
Seven repos scored. Seven repos with HAS_LICENSE=no. Your COVID mortality research is freely discoverable but legally unreusable. Schrödinger's open science.
CI Is a Myth
Not a single CI pipeline across the entire portfolio. Your Lee-Carter forecasting needs ~70GB RAM to run but apparently zero bytes for a GitHub Actions YAML.
Burst Coder
alcohol2 was born and nearly complete in 19 minutes on May 6, 2026. Your heatmap shows 18 empty weeks followed by max-4 bursts. You don't write code — you channel it.
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% weight56D
- Consistency20% weight60C
- Quality20% weight57D
- Depth15% weight65C
- Breadth10% weight45D
- Community10% weight50D
03 · Stats
365-day commit heatmap
56 active days
Language distribution
- HTML78%
- R19%
- TeX3%
- Stan0%
- Makefile0%
- Shell0%
04 · Numbers
Owned repos
non-fork
94
Commits
last 12 months
295
Followers
136
Joined GitHub
Feb 2015
05 · Top repos
jschoeley /
bhump
Research analysis of perinatal mortality patterns using parametric survival modeling. R-based statistical project with life-table construction, competing-risks modeling, and reproducible analysis pipeline via Makefile. HAS_README=yes but README minimal; well-structured src/ and strong architectural scope (25.5MB codeba
jschoeley /
demoscapes
Full-stack Node.js + MongoDB demographic data visualization platform with REST API, structured multi-file architecture, and Docker Compose orchestration. Has README, typed environment, and meaningful build/deployment pipeline, but lacks tests and CI.
jschoeley /
e0deficit
Research data pipeline analyzing COVID-19 life expectancy deficits across 34 countries using STMF mortality data, with structured multi-file R codebase, config-driven analysis, and comprehensive output (SVGs, CSVs, RDS files).
jschoeley /
xsexratio
R research project analyzing COVID-era excess mortality patterns by sex across 38 countries, 2020–2023. Comprehensive epidemiological pipeline with 9+ statistical models and Bayesian model averaging, structured analysis outputs, but minimal ecosystem adoption and no automated testing infrastructure.
jschoeley /
xfertility
Research analysis repo computing excess/deficit births during COVID-19 across European regions. Well-structured R scripts with multi-file pipeline (GAM models, Bayesian stacking, statistical analysis), typed data structures, and meaningful README documenting the paper. No tests, CI, or license; sparse commit history (4
jschoeley /
alcohol2
Research-focused R project implementing penalized Lee-Carter mortality forecasting for alcohol-related excess death estimation. Single commit on repo created 2026-05-06, minimal README, ~12MB codebase with structured analysis pipeline but no tests, CI, or license.
jschoeley /
epc26os
Educational lecture materials repo for EPC 2026 conference on Open Science in Demography. Contains slides and hands-on Git/GitHub course, but minimal actual code or executable artifacts.
06 · Timeline
- Feb 7, 2015Joined GitHub
- Dec 2, 2021Created xfertility
- May 25, 2023Created bhump — The birth-hump – a shape decomposition of perinatal excess mortality
- Dec 14, 2023Created xsexratio — Temporal Dynamics of Sex Differences in Excess Mortality
- Mar 30, 2025Created e0deficit — Life expectancy deficits since COVID-19
- Jan 23, 2026Created demoscapes
- Mar 10, 2026Created epc26os
- May 6, 2026Created alcohol2 — International estimates of alcohol related excess mortality since 2020
- May 6, 2026Most recent push to alcohol2
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.