01 · Roasts
Sprint Merchant
6 out of 7 repos were created within a 4-month window in 2026, several within single sessions (Tradingalgz: 2 commits in 37 minutes). You're not building software — you're speedrunning the GitHub commit graph.
Architect Without Tests
Coresense-Backend- has an ARCHITECTURE.md, a STATUS.md, a design.md, AND a docs/ folder — but only one repo with actual tests across the whole profile. You document the cathedral; you just don't verify it holds up.
The Truncation Graveyard
Tradingalgz has backtest.py, live_engine.py, and web/app.py all cut off mid-function. That's not a trading system, that's a proof-of-concept that ran out of RAM mid-paste.
1 Star, 6 READMEs
Total stars across 12 public repos: 1. You've written more documentation explaining what these projects will do than commits actually making them do it.
Ghost Town Heatmap
49 out of 52 weeks on your public heatmap are completely dark. privateWorkLikely=true saves your Consistency score, but the public face of this account looks like it only woke up in April 2026.
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% weight55D
- Breadth10% weight65C
- Community10% weight25F
03 · Stats
90-day commit heatmap (public events only)
7 active days
Language distribution
- Python40%
- TypeScript30%
- JavaScript20%
- CSS10%
04 · Numbers
Owned repos
non-fork
12
Commits
last 12 months
113
Followers
1
Joined GitHub
Jul 2022
05 · Top repos
Tosin-A /
Coresense-Backend-
FastAPI personal AI coach backend with Supabase integration, multi-router architecture, health insights engine, and message limits. Typed Python with structured modular design, comprehensive docs (README + ARCHITECTURE.md + STATUS.md + design.md), and tests present.
Tosin-A /
portfolio-website
Personal portfolio website showcasing multiple shipped projects (Coresense, CloutAI, Calitrack). Typed TypeScript + structured src/, HAS_CI with quality checks, but lacks tests and is young (created 2026-04-07, 10 commits in ~10 days).
Tosin-A /
Cora-Lockin
TypeScript AI coaching platform with React Native frontend and FastAPI backend. Well-documented with design artifacts and structured architecture, but no CI, no license, 0 stars, and no source files sampled to verify implementation quality.
Tosin-A /
coresense-landing
A React 19 landing page for CoreSense AI health app with clean component structure, responsive design, and GitHub Pages CI/CD. Zero stars/forks suggests early-stage project; untyped JavaScript and no tests limit quality despite solid documentation and working tooling.
Tosin-A /
Typist
Early-stage typing practice desktop app with gamified curriculum, adaptive difficulty, and cloud leaderboard support. Unfinished onboarding flow and missing key backend methods limit current usability despite solid architecture and CI/CD setup.
Tosin-A /
rag-hybrid
Educational hybrid RAG prototype combining dense (Chroma) + sparse (BM25) retrieval with RRF fusion and Ollama LLM integration. Well-documented with typed Python code but minimal project history (3 commits, <1 hour old).
Tosin-A /
Tradingalgz
Incomplete ML + ICT futures trading system (NQ/ES) combining rule-based and deep learning; typed Python with README but no tests/CI/license, truncated files, 0 adoption, single-session commit. Experimental dump.
06 · Timeline
- Jul 12, 2022Joined GitHub
- Dec 10, 2025Created coresense-landing — CoreSense landing page - AI health coach app
- Jan 6, 2026Created Cora-Lockin
- Jan 6, 2026Created Coresense-Backend-
- Apr 7, 2026Created portfolio-website — Personal portfolio website (Vite, React, Tailwind)
- Apr 8, 2026Created Tradingalgz
- Apr 15, 2026Created rag-hybrid — Local hybrid RAG: dense (ChromaDB + sentence-transformers) + sparse (BM25) retrieval fused with Reciprocal Rank Fusion, answered by Ollama mistral
- Apr 16, 2026Created Typist — Adaptive typing practice app — electric blue, per-key error tracking, auto-adaptive sessions
- Apr 21, 2026Most recent push to Typist
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.