01 · Roasts
CI, but make it lonely
xfetch runs Playwright benchmarks every six hours, yet has no test suite. The benchmark has more commitment than the assertions.
Pre-alpha permissions speedrun
datarola's Firestore rule is literally `if true`; your database has achieved radical openness before product-market fit.
Practice empire
175 multi-repo-volume commits and 427 yearly commits prove you ship. Too much of the visible output is still interview practice dressed as a portfolio.
Portfolio loading…
ThinkerDesigns.github.io is 4 KB and says “My projects.” It is technically honest, if not aggressively informative.
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% weight55D
- Community10% weight50D
03 · Stats
365-day commit heatmap
169 active days
Language distribution
- C++46%
- Python12%
- HTML9%
- Jupyter Notebook9%
- CMake8%
- TypeScript8%
- Other8%
04 · Numbers
Owned repos
non-fork
40
Commits
last 12 months
427
Followers
29
Joined GitHub
Mar 2020
05 · Top repos
ThinkerDesigns /
xfetch
xfetch is a substantial typed Next.js scraping product prototype with documented architecture, Playwright benchmark automation, and multi-stage extraction code, but it has no stars, tests, license, or demonstrated external adoption.
ThinkerDesigns /
datarola
DataRola is a documented, typed Next.js 15 prototype with Firebase-backed ingestion, multiple connector integrations, text-to-SQL, charts, and anomaly detection, but has no adoption signals, tests, CI, or license and retains serious pre-alpha security and completeness gaps.
ThinkerDesigns /
neetcode-submissions
A NeetCode GitHub Sync archive with a clear README and topic/problem organization, but no tests, CI, typing, license, or evidence of external adoption; sampled solutions are mostly straightforward interview-practice implementations.
ThinkerDesigns /
codepath
A documented CodePath DSA practice repository with nested unit/session exercises, but no visible adoption, tests, CI, typing, license, or packaging; sampled code is instructional and includes a duplicate function definition.
ThinkerDesigns /
leetcode
A small beginner LeetCode solution collection with 30 sampled commits and several recognizable algorithm implementations, but no visible adoption, tests, CI, license, or repository tooling.
ThinkerDesigns /
reviewer
A documented single-file browser resume reviewer with PDF/DOCX/TXT parsing and configurable Ollama, Anthropic, or OpenAI backends, but no visible tests, CI, license, or external adoption.
ThinkerDesigns /
projecteuler
A beginner Project Euler solution collection with several standalone Python and Java files, but minimal documentation, no tests or CI, and visible correctness and organization issues.
ThinkerDesigns /
ThinkerDesigns
A minimal GitHub profile README repository with 2 stars and no sampled source files, tests, CI, license, or typed implementation.
ThinkerDesigns /
ThinkerDesigns.github.io
A minimal personal GitHub Pages-style scaffold: index.html contains only the text “My projects,” with no documented project content or supporting repository infrastructure.
06 · Timeline
- Mar 11, 2020Joined GitHub
- Dec 19, 2021Created ThinkerDesigns
- Jul 23, 2022Created ThinkerDesigns.github.io
- Sep 11, 2025Created projecteuler — My solutions to problems as a beginner
- Nov 9, 2025Created leetcode — my leetcode solutions as a beginner
- Jun 3, 2026Created codepath
- Jun 3, 2026Created neetcode-submissions — My NeetCode.io problem submissions
- Jul 2, 2026Created xfetch
- Jul 9, 2026Created datarola
- Jul 14, 2026Created reviewer — A website built to score your SWE resume
- Sep 15, 2026Most recent push to leetcode
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.