01 · Roasts
Portfolio, not pull requests
The portfolio advertises five products, but all scored repos are still sitting at 0 stars and 0 forks.
Tests know the way
resume-toolkit and ai-github-toolkit brought CI and real tests; most of the practice fleet skipped both.
Sprint-heavy history
Several repos were created and last pushed the same day—great prototypes, weak evidence of long-haul maintenance.
PR counter is doing cardio
197 PRs this year is serious motion, but the supplied data cannot show which ones landed outside your own orbit.
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% weight50D
- Quality20% weight67C
- Depth15% weight50D
- Breadth10% weight80A
- Community10% weight50D
03 · Stats
365-day commit heatmap
69 active days
Language distribution
- JavaScript30%
- Python22%
- Dart19%
- TypeScript13%
- Java10%
- CSS3%
- Other3%
04 · Numbers
Owned repos
non-fork
12
Commits
last 12 months
444
Followers
17
Joined GitHub
Feb 2019
05 · Top repos
Abuubkar /
ai-github-toolkit
A polished early-stage Python toolkit packaging four AI GitHub automation tools, with reusable composite-action wiring, mocked provider/API tests, config validation, and CI, but no observable adoption yet.
Abuubkar /
resume-toolkit
A thoughtfully designed local-first resume tailoring toolkit with CLI, MCP workflow, provenance checks, multi-format rendering, and strong integration/unit coverage, but currently a same-day, zero-star JavaScript project without demonstrated external adoption.
Abuubkar /
abuubkar.github.io
A polished, typed Next.js portfolio with a documented design system, reusable section/component architecture, keyboard navigation, analytics, and GitHub Pages deployment, but no visible tests, license, stars, or external adoption evidence.
Abuubkar /
react-concepts
A small React 19/Vite interview-prep lab with four interactive hook and reconciliation demos, URL state synchronization, and ESLint configuration, but no tests, CI, license, or evidence of adoption.
Abuubkar /
object-detection
A small Vite browser demo using Transformers.js and Xenova/yolos-tiny for image object detection, with percentage-based bounding-box rendering but no tests, CI, license, or external adoption evidence.
Abuubkar /
ai-learning
Small JavaScript CLI RAG prototype using OpenAI embeddings, Supabase vector search, and chat completion; it has a basic README and modular services but no tests, CI, license, or demonstrated adoption.
Abuubkar /
open-router-practice
A small documented Vite chat client integrating OpenRouter streaming, Markdown rendering, and DOMPurify, but it has no tests, CI, license, typed code, or evidence of adoption and was created in a one-commit burst.
Abuubkar /
ollama-practice
A documented but very small Express/Ollama practice app: one endpoint forwards a query to Mistral, with no tests, CI, license, or evidence of adoption.
Abuubkar /
Abuubkar
A 3 KB GitHub profile README presenting a senior full-stack résumé, but no source files, product, tests, CI, license, or evidence of adoption.
06 · Timeline
- Feb 24, 2019Joined GitHub
- Jun 4, 2026Created abuubkar.github.io
- Jun 16, 2026Created Abuubkar
- Jun 18, 2026Created react-concepts
- Jul 11, 2026Created ai-learning
- Jul 12, 2026Created object-detection
- Jul 12, 2026Created ollama-practice
- Jul 14, 2026Created open-router-practice
- Jul 15, 2026Created ai-github-toolkit
- Aug 1, 2026Created resume-toolkit — Turn one canonical career profile into a job-specific, provenance-checked resume. Local-first, agent-driven.
- Sep 1, 2026Most recent push to abuubkar.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.