01 · Roasts
Portfolio, not audience
Eight named products are shipping, but 11 total stars and 3 followers mean the crowd has not arrived yet.
Test-suite flex
LeadForge’s 198 checks, NoteMind’s 173, and RetailFlow’s 231 are serious receipts; several neighboring repos forgot to RSVP.
Fresh concrete
147 recent sampled commits show high output, but many flagship repos were born only weeks ago—let them survive a few seasons.
CI roulette
RetailFlow brings 231 tests with no CI, while MindScribe brings neither tests nor CI. Automation should not be optional DLC.
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% weight68C
- Consistency20% weight65C
- Quality20% weight81A
- Depth15% weight58D
- Breadth10% weight65C
- Community10% weight25F
03 · Stats
365-day commit heatmap
43 active days
Language distribution
- TypeScript64%
- JavaScript26%
- Java5%
- PLpgSQL4%
- CSS1%
- Python0%
04 · Numbers
Owned repos
non-fork
10
Commits
last 12 months
289
Followers
3
Joined GitHub
Jul 2025
05 · Top repos
Ahmadhsn1 /
notemind-ai
NoteMind is a documented MERN AI note platform with semantic search, cited cross-note Q&A, flashcards, wikilinks, signed uploads, session revocation, and a substantial automated security/integration test suite.
Ahmadhsn1 /
leadforge-ai
A documented, typed Next.js/NestJS sales-intelligence monorepo with evidence-grounded AI, deterministic scoring, guarded outreach, substantial tests, and multi-service CI; adoption is currently minimal at 1 star.
Ahmadhsn1 /
Rag-saas-RetrivoVault
A documented, typed RAG SaaS with React/TypeScript, Express/MongoDB vector retrieval, streaming citations, billing, quotas, security hardening, tests, and CI; adoption is not yet demonstrated by its 0 stars or forks.
Ahmadhsn1 /
retailflow-saas
RetailFlow is a documented, typed Next.js/Supabase retail platform with substantial POS, inventory, khata, RLS, audit, reconciliation, and concurrency-focused implementation, but it has only 1 star and no CI evidence.
Ahmadhsn1 /
SpendSmart
SpendSmart is a documented, typed Java Android expense tracker with Firebase Auth/Firestore, live listeners, server-side security rules, and a reproducible build/lint workflow, but it has only 1 star and no tests.
Ahmadhsn1 /
larder-concierge-ai
A polished, deployed Copper Larder hospitality concierge with a grounded Gemini/Supabase architecture, deterministic cost controls, streamed chat, lead capture, dashboard, and strong documentation; adoption remains limited at 1 star and 0 forks.
Ahmadhsn1 /
fittrack-gym-management
A polished React 19/Vite gym-management front end with eight routes, in-memory CRUD, Recharts analytics, responsive custom CSS tokens, and strong architecture documentation, but only 1 star, no tests, and no persistence.
Ahmadhsn1 /
Ahmadhsn1
A polished profile README repo with custom animated SVG branding and credible product claims, including EasyQuran on both major app stores and 10,000+ users, but limited repository-level engineering artifacts.
Ahmadhsn1 /
MindScribe-android-app
A documented Java/Material Android journaling app with Firebase-backed notes, biometric locking, offline image-upload scheduling, mood analytics, and restrictive Firebase rules, but only a one-day commit burst and no tests or CI.
06 · Timeline
- Jul 13, 2025Joined GitHub
- Jul 11, 2026Created notemind-ai — AI-augmented MERN note-taking platform — cross-note Q&A with cited sources, semantic search, spaced-repetition flashcards, and a wikilink graph. Google Gemini. Engineered to produc
- Jul 25, 2026Created retailflow-saas — Multi-tenant retail POS, inventory and khata (credit ledger) platform for South Asian shops. Next.js 15 + Supabase Postgres, with tenant isolation enforced in the database by Row L
- Aug 13, 2026Created Ahmadhsn1 — AI Systems Engineer · Full-Stack · Native Android — LLM products end to end. Profile README.
- Aug 19, 2026Created larder-concierge-ai — Hannah, an AI front-of-house concierge for hospitality sites — streamed Gemini replies behind a deterministic cost/guardrail pipeline. Next.js 16, React 19, Supabase.
- Aug 23, 2026Created MindScribe-android-app — Privacy-first Android journaling app — biometric app lock, offline-first Firebase sync, mood analytics, and guided daily prompts. Java + Material Design 3.
- Aug 23, 2026Created fittrack-gym-management — Gym management dashboard built with React 19, Vite and Recharts. Eight routes, full CRUD, dual-theme design token system and zero UI dependencies.
- Aug 23, 2026Created SpendSmart — Real-time personal expense tracker for Android — Java, Firebase Auth + Cloud Firestore, Material 3. No backend server: Firestore Security Rules are the authorization layer.
- Sep 8, 2026Created leadforge-ai — AI sales-intelligence platform: finds local businesses, explains why each is worth contacting with citable evidence, and drafts the message you would actually send. Next.js 15 + Ne
- Sep 9, 2026Created Rag-saas-RetrivoVault — The research assistant that only knows what you've read — a production-grade, individual-focused RAG SaaS. Streaming, citation-backed answers over your own documents. Node + Expres
- Sep 9, 2026Most recent push to Rag-saas-RetrivoVault
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.