01 · Roasts
Heatmap Archaeologist
Your GitHub heatmap is 36 weeks of digital silence followed by a frantic burst. GitHub wasn't your coding environment — it was your confession booth at semester's end.
Hackathon Hoarder
Three hackathon repos (algothon, GDG-Hackathon, chain-reaction), none with CI, none with tests beyond one. You ship fast and disappear faster — great for trophies, rough for maintainability.
README Roulette
4 out of 10 repos have no README whatsoever. One of your READMEs is literally just a title. Your code can't advocate for itself if you won't write a single paragraph about it.
Type Hint Denier
Python appears in 25% of your codebase and you typed exactly zero function signatures across trading-bot, neetcode, chain-reaction, and write_code. FastAPI is literally built on type hints. This is personal.
Solo Operator
94% solo commits across 213 sampled commits. You've opened 30 PRs this year but apparently none of them were to your own repos — because there's nobody else to review them.
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% weight65C
- Quality20% weight57D
- Depth15% weight58D
- Breadth10% weight80A
- Community10% weight50D
03 · Stats
365-day commit heatmap
49 active days
Language distribution
- TypeScript28%
- Python25%
- JavaScript20%
- Jupyter Notebook13%
- CSS6%
- C++3%
- Other5%
04 · Numbers
Owned repos
non-fork
15
Commits
last 12 months
359
Followers
13
Joined GitHub
Sep 2023
05 · Top repos
mideyy7 /
musicmate
University-focused music matching social app with React 19 + FastAPI backend. Full-stack implementation with Spotify auth, real-time matching, chat, playlists. No production users yet (0 stars); personal/university project in active development phase.
mideyy7 /
algothon
Hackathon submission for Imperial Algothon 2026 trading bot competition. Well-structured Python project with sophisticated statistical arbitrage strategies and live data pipeline for London markets (tides, weather, flights). 14.4k codebase, no tests/CI, typed language with clear architectural separation. Recent activit
mideyy7 /
GDG-Hackathon
DevCore is a monorepo implementing an agentic software delivery system with generator/reviewer agent loops, planning, and GitHub integration. Early-stage product (1 star, <1 month old), shipped with TypeScript, tests, and multi-service architecture but lacks CI/CD and production hardening.
mideyy7 /
chain-reaction
Hackathon MVP combining supply-chain forecasting (LightGBM), graph modeling (NetworkX), and Solana audit trail. Untyped Python, no tests/CI, but comprehensive documented system (backend + frontend + ML) shipped in single day with working API and UI.
mideyy7 /
trading-bot
Educational trading bot using moving average crossover strategy with FastAPI frontend and Binance integration. Untyped Python, minimal README, no tests/CI/license, but functional modular architecture across strategy, engine, execution, and backtesting components.
mideyy7 /
neetcode
Auto-synced NeetCode problem submissions (~46 KB, 30 commits) with minimal structure. No tests, CI, or type hints; Python submissions lack type annotations despite TYPED_LANG=no. README explains platform integration but repo is primarily a submission dump.
mideyy7 /
f1-telemetry
Early-stage F1 telemetry simulation in C++ with race control logic (penalty enforcer, track limits monitoring), multi-threaded ring buffer. Minimal stars/adoption, sparse README, 8 commits in one week with no tests or CI.
mideyy7 /
google_cloud
Minimal experimental repo with 26 KB codebase, no README, tests, CI, or license. Created Feb 2026, shows 22 of last 30 commits but lacks documentation and structure. Early-stage scaffold with no discernible purpose or polish.
mideyy7 /
smartbee
Minimal JavaScript project created in Feb 2026 with no documentation, tests, CI, license, or gitignore. 8 commits across 2.5 weeks with 12.3MB size suggests some code present, but lack of README and all quality signals indicates experimental scaffold.
mideyy7 /
write_code
Minimal Python practice repo created on 2026-03-28 with 12 KB and 14 commits over ~2.5 hours. No README, tests, CI, docs, license, or gitignore. Appears to be a scratch/learning exercise with no observable structure or output.
06 · Timeline
- Sep 6, 2023Joined GitHub
- Dec 28, 2025Created trading-bot — A Trading Bot
- Jan 28, 2026Created f1-telemetry
- Feb 8, 2026Created chain-reaction
- Feb 10, 2026Created musicmate
- Feb 20, 2026Created smartbee
- Feb 25, 2026Created google_cloud
- Feb 27, 2026Created algothon — Imperial Algothon 2026
- Mar 13, 2026Created GDG-Hackathon
- Mar 28, 2026Created write_code — Practice
- Mar 30, 2026Created neetcode — My NeetCode.io problem submissions
- Apr 24, 2026Most recent push to neetcode
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.