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#118 — Top 93.2%

TahaKhanM

Muhammad Taha

B

Solid engineer

Overall

0.0

/ 100

01 · Roasts

Hibernation Champion

22 consecutive empty weeks on your heatmap, then frantic burst-mode coding. Your GitHub looks like a bear that wakes up every few months to build a 50k-LOC Rust engine.

2 Followers, Infinity Ambition

You've shipped a Chrome extension with pgTAP database tests, a top-5 Citadel terminal bot, and a globally-ranked trading system — and somehow convinced exactly 2 people to follow you. Marketing budget: $0.

Test Coverage: Selective

zetalog has Playwright E2E running real Chromium 3x + pgTAP DB tests. foodbank-optimisation has... 200 lines in one function and vibes. The variance on this profile is genuinely alarming.

Solo Artist, No Features

soloPct = 100%. Every single commit, every repo, zero collaborators. CitadalTerminal beat Georgia Tech's team. You're out here playing 1v5 and calling it a fair fight.

The Profile README

TahaKhanM repo scored a 20 — the lowest on your entire profile. Your personal brand repo is your weakest shipped artifact. The irony is not lost.

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

  • Impact
    25% weight
    68C
  • Consistency
    20% weight
    65C
  • Quality
    20% weight
    77B
  • Depth
    15% weight
    70B
  • Breadth
    10% weight
    65C
  • Community
    10% weight
    30F

03 · Stats

365-day commit heatmap

57 active days

Less
More

Language distribution

7 langs
  • Python52%
  • Jupyter Notebook28%
  • TypeScript14%
  • Rust2%
  • HTML1%
  • JavaScript1%
  • Other2%

04 · Numbers

Owned repos

non-fork

11

Commits

last 12 months

978

Followers

2

Joined GitHub

Oct 2020

05 · Top repos

TahaKhanM /

CitadelTerminal

70/100

Production-grade competition AI with ~50k LOC: Rust simulator engine reverse-engineered from bytecode + Python search loop. Top-5 placing in 1,000+ competitor tournament, comprehensive documentation, no tests/CI but typed Rust/Python code with architectural clarity.

I65Q80D65
README
Python12mo ago

TahaKhanM /

Prosperity

63/100

Prosperity 4 IMC trading competition workspace: 329 MB Rust/Python backtester, options pricing suite, market-making traders, counterparty analysis. Team peaked #32 globally. Well-documented (design.md, ARCHITECTURE.md, STATUS.md) but no tests/CI/license.

I55Q65D70
README
Python02mo ago

TahaKhanM /

zetalog

62/100

ZetaLog: a Chrome extension + web leaderboard for Zetamac mental-arithmetic game. Validates game telemetry server-side with rigorous anti-cheat (consistency, physiology, statistical problem-stream checks), uses typed Zod schemas throughout, ships with tests (HAS_TESTS=yes), CI (HAS_CI=yes), and extensive docs (design.m

I55Q80D50
READMETestsCITyped
TypeScript01mo ago

TahaKhanM /

AI-Agent-Hackathon

60/100

Precedent: Enterprise incident-resolution agent with deterministic policy engine, ACL-gated knowledge retrieval, typed tool execution, and hash-chained audit. Measured against real ServiceNow data (94.4% fix-class repeatability). Comprehensive architecture, tests, and CI—but nascent (3 weeks old, 0 GitHub stars).

I40Q75D65
READMETestsCI
Python02mo ago

TahaKhanM /

FoundersHQ

52/100

Full-stack fintech MVP with deterministic financial core, evidence-linked insights, and LLM guardrails. Hackathon winner with typed Python backend, CI/tests, but 0 stars and pre-launch product focus.

I40Q65D50
READMECITyped
TypeScript02mo ago

TahaKhanM /

ascendra

50/100

Gamified career-prep platform with multi-judge AI scoring pipeline and Elo ratings. FastAPI backend (Python, no type hints) + Next.js frontend, structured 14 bounded contexts, comprehensive docs, 13 commits over 3 months. Active portfolio project shipped beyond hackathon MVP.

I40Q60D50
READMETestsCI
Python02mo ago

TahaKhanM /

led-panel-pong-emulator

48/100

Educational coursework project: C Pong game + faithful browser emulator for 32×32 RGB LED panel protocol. Well-documented architecture with HAL abstraction, Emscripten integration, and debug features; unfinished game logic and no tests/CI limit production readiness.

I25Q60D50
README
C03mo ago

TahaKhanM /

neural-network-from-scratch

38/100

Educational NumPy neural network on MNIST in single Python file with comprehensive mathematical documentation in README, but lacks tests, CI, types, and production structure.

I25Q42D48
README
Jupyter Notebook03mo ago

TahaKhanM /

foodbank-optimisation

35/100

Academic research implementation using PuLP to solve MILP for nutritionally constrained, cost-minimized food bank parcels. Code is functional but minimally documented, lacks tests/CI, and has shallow version control history (2 of last 30 commits).

I25Q45D35
README
Python03mo ago

TahaKhanM /

microfinance-preprint-repo

33/100

Academic research preprint repository with pandas/scikit-learn analysis of microfinance impact on female employment in India. Python scripts directly transcribed from notebooks; no tests, CI, or typed code. Structured for reproducibility but thin on engineering practices.

I25Q40D35
README
Python03mo ago

TahaKhanM /

TahaKhanM

20/100

GitHub profile README showcasing CS student's technical interests and skills. Purely informational portfolio page with no code, no examples, no structure—a one-off placeholder repo.

I15Q25D20
README
Unknown03mo ago

06 · Timeline

  1. Oct 31, 2020
    Joined GitHub
  2. Sep 8, 2025
    Created neural-network-from-scratch — NumPy neural network from scratch with SGD/backpropagation on MNIST.
  3. Feb 6, 2026
    Created microfinance-preprint-repo — pandas/scikit-learn analysis of microfinance, MFI operations, and women's employment outcomes.
  4. Feb 6, 2026
    Created foodbank-optimisation — Linear-programming optimisation model for nutritionally constrained, lower-cost food bank parcels.
  5. Feb 6, 2026
    Created led-panel-pong-emulator — C Pong game and browser emulator for a 32x32 RGB LED panel protocol.
  6. Feb 21, 2026
    Created TahaKhanM — GitHub profile README for Taha Khan's technical portfolio.
  7. Feb 28, 2026
    Created FoundersHQ — Full-stack fintech platform for startup invoices, runway forecasting, search, REST APIs, and OpenAPI docs.
  8. Mar 28, 2026
    Created ascendra — Gamified, competitive career-prep & candidate-benchmarking platform — pathway arenas, calibrated multi-judge AI scoring, Elo ratings, skill tree, and replays. FastAPI + Next.js.
  9. Apr 12, 2026
    Created Prosperity — IMC Prosperity trading workspace: options pricing, market making, statistical arbitrage, Rust/Python backtesting.
  10. Apr 23, 2026
    Created CitadelTerminal — Citadel Terminal AI challenge workspace with Python strategies, replay analysis, and Rust simulation tooling.
  11. Jul 2, 2026
    Created AI-Agent-Hackathon
  12. Aug 9, 2026
    Created zetalog
  13. Aug 17, 2026
    Most recent push to zetalog

07 · Compare

github.com/
TahaKhanM · 6dmedian coder

08 · Rubric

How this score was produced

Overall = Σ (category × weight) + gentle top-end curve

CategoryWeightScoreContrib.
Raw total65.4
Top-end curve+5.7
Final overall71.1

Tier thresholds

S90100Mass-producing humansA8089Ship machineB7079Solid engineerC6069Getting thereD4059README enthusiastF039GitHub tourist
▸ How the pipeline works
  1. 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.
  2. 02Triage.A small model reads every repo's file tree + README and picks the 20 files per repo that actually reveal how you code.
  3. 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.
  4. 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.
  5. 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.
TahaKhanM · 71.1/100 — Rate My GitHub