01 · Roasts
Portfolio, meet proof
Seven named projects are doing impressive résumé cardio, but the account has 3 total stars and 0 forks.
CI sighting
carebells has a signed-APK workflow; most of the rest of the portfolio still treats CI like classified avionics data.
Test bench pending
TriFlight documents bench protocols and UAV failure detection reports strong synthetic F1s, yet both repos ship with no test suite.
Jarvis carries
jarvis brings FastAPI, Next.js, Postgres, Redis, n8n, and Docker; it is currently the portfolio's most convincing grown-up subsystem.
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% weight62C
- Consistency20% weight60C
- Quality20% weight57D
- Depth15% weight55D
- Breadth10% weight55D
- Community10% weight25F
03 · Stats
365-day commit heatmap
63 active days
Language distribution
- Python56%
- HTML24%
- TypeScript14%
- Java3%
- PLpgSQL1%
- C++1%
- Other1%
04 · Numbers
Owned repos
non-fork
9
Commits
last 12 months
89
Followers
0
Joined GitHub
Dec 2024
05 · Top repos
amaannizam29 /
jarvis
A documented, MIT-licensed self-hosted Jarvis stack with FastAPI, Next.js, PostgreSQL/pgvector, Redis, n8n, voice, memory, career tooling, and Windows control; substantial architecture but only 2 stars and no CI or runtime test suite.
amaannizam29 /
carebells
A small, documented Android Java WebView kiosk with CI-based signed APK builds and practical device/session controls, but no tests, license, external adoption, or substantial repository history.
amaannizam29 /
triflight-avionics-research
A documented pre-experimental UAV avionics research repo with a functional read-only MAVLink-to-CSV logger, architecture and bench-test documentation, but no reported hardware validation, tests, CI, or external adoption.
amaannizam29 /
vehicle-rental-system-java
A documented Java console rental application with 10-class OOP structure, sample data, rental/return workflows, and discount calculation; it is a small educational project without tests, CI, license, or visible adoption.
amaannizam29 /
AI-Disease-Prediction-System
A small MIT-licensed Python prototype combining local BERT disease classification with GPT-4 follow-up and retraining workflows, but with 1 star, no tests/CI, untyped code, and notable run-readiness issues.
amaannizam29 /
uav-failure-detection
A substantial, documented UAV fault-detection prototype combining synthetic multi-label ML, deterministic safety policy, dashboards, and MAVLink replay/live integration, but with no tests or CI and no demonstrated external adoption.
amaannizam29 /
Germany-Traffic-Light-System
A documented Arduino traffic-light project with basic and advanced .ino implementations, RGB LED sequencing, pedestrian controls, request LED, and buzzer integration, but no tests or CI and limited project scope.
amaannizam29 /
amaannizam29
A maintained GitHub profile README that clearly presents seven named projects, deployed products, awards, and technical focus, but the repository itself contains no sampled implementation files or adoption metrics.
amaannizam29 /
uav-integration-hardware
A documented, MIT-licensed CAD component collection with three named UAV integration parts, but no stars, forks, tests, CI, or demonstrated external adoption.
06 · Timeline
- Dec 14, 2024Joined GitHub
- Dec 14, 2024Created Germany-Traffic-Light-System — Arduino-Powered Traffic Light System with Pedestrian Control and Buzzer Integration
- Dec 14, 2024Created amaannizam29 — Config files for my GitHub profile.
- Dec 19, 2024Created AI-Disease-Prediction-System — AI Disease Prediction System: An intelligent tool that predicts diseases based on symptoms using a local BERT-based model and GPT-4 refinement. Features interactive follow-up quest
- Apr 25, 2026Created triflight-avionics-research — Pre-experimental UAV avionics architecture, MAVLink telemetry logger, and validation framework
- Jun 13, 2026Created jarvis — Self-hosted personal AI assistant — voice, persistent memory, agentic tools, career copilot, and Windows desktop control. NVIDIA NIM + Groq + OpenAI fallback. Docker one-command de
- Jun 20, 2026Created uav-failure-detection — Multi-fault predictive failure detection for UAVs: ML detection of battery, GPS, compass, and motor faults from MAVLink telemetry, with a safety-aware operator console and live com
- Jun 21, 2026Created uav-integration-hardware — Custom CAD components for integrating avionics and power onto a VTOL UAV airframe: vibration-aware lift-motor mounts and a cam-locked battery tray for CG stability through transiti
- Jun 22, 2026Created carebells — carebells application for testing
- Jun 24, 2026Created vehicle-rental-system-java — Console-based Vehicle Rental System built in Java using Object-Oriented Programming principles including inheritance, polymorphism, composition, and aggregation. Supports vehicle m
- Jul 7, 2026Most recent push to vehicle-rental-system-java
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.