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#206 — Top 88.2%

FiNdAlMkSkInDaL

Finlay Phillips

C

Getting there

Overall

0.0

/ 100

01 · Roasts

Portfolio, not pull requests

Eight named projects and 524 yearly commits, but 0 PRs, 0 issues, 0 stars, and 0 forks: the shipping is real; the outside feedback loop is not.

CI is selective

tickforge and Polymarket_bot automate checks, while Macro-Bias, Identity, and the flagship portfolio still leave reliability to optimism.

The zero-star paradox

Macro Bias has pricing routes, TickForge has a live Explorer, and Toolbox has a domain—yet the dashboard still reads 0 stars across the board.

Horizontal builder detected

166 recent commits sampled across repos and a 232 MB Polymarket_bot say this is far beyond a one-repo tutorial arc.

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
    62C
  • Consistency
    20% weight
    65C
  • Quality
    20% weight
    71B
  • Depth
    15% weight
    58D
  • Breadth
    10% weight
    80A
  • Community
    10% weight
    25F

03 · Stats

365-day commit heatmap

68 active days

Less
More

Language distribution

7 langs
  • Python70%
  • TypeScript20%
  • Rust7%
  • C++1%
  • Shell0%
  • CSS0%
  • Other2%

04 · Numbers

Owned repos

non-fork

9

Commits

last 12 months

524

Followers

2

Joined GitHub

Aug 2024

05 · Top repos

FiNdAlMkSkInDaL /

tickforge

55/100

A documented C++23 limit-order-book project with matching, self-trade prevention, Avellaneda–Stoikov simulation, browser demo, tests, benchmarks, and cross-platform CI; adoption is currently unproven at 0 stars.

I28Q74D45
READMETestsCI
C++02mo ago

FiNdAlMkSkInDaL /

Polymarket_bot

54/100

A substantial, documented Polymarket shadow-research stack with live L2 Parquet capture, backtesting, multi-signal orchestration, risk guards, hourly lanes, and Telegram telemetry, but no visible adoption or licensing.

I20Q68D55
READMETestsCI
Python01mo ago

FiNdAlMkSkInDaL /

Macro-Bias

48/100

Typed Next.js/Supabase macro-regime product with stocks and crypto KNN research, walk-forward evaluation, paper ledgers, publishing integrations, and substantial schema-backed application structure; adoption remains unproven at 0 stars.

I30Q62D50
READMETyped
TypeScript02mo ago

FiNdAlMkSkInDaL /

latent-control-lab

47/100

A well-documented research demo that routes frozen distilgpt2 activations through a tested linear probe into a sandboxed 5×5 VectorBot, but has no visible adoption or external product evidence.

I20Q70D50
READMETestsCI
Python02mo ago

FiNdAlMkSkInDaL /

FiNdAlMkSkInDaL.github.io

44/100

A deployed, highly designed GitHub Pages portfolio that bundles six interactive project demos, shareable routes, CV downloads, and a polished pixel-garden interface, but has no visible external adoption or automated tests.

I36Q45D50
READMECI
CSS01mo ago

FiNdAlMkSkInDaL /

Identity

44/100

A substantial, well-documented Rust Windows prototype implementing local capture, SQLite transit processing, protected storage, memory graphs, vector backends, and scoped context generation, but with no visible adoption, CI, or license.

I20Q62D50
READMETyped
Rust02mo ago

FiNdAlMkSkInDaL /

asof

34/100

A focused, well-documented Python reconciliation tool with cassette replay, SQLite state, a rule-driven policy, and extensive tests, but no visible adoption, CI, or typed-language status.

I20Q60D20
READMETests
Python01mo ago

FiNdAlMkSkInDaL /

FiNdAlMkSkInDaL

30/100

A maintained personal portfolio README linking five named engineering projects and a GitHub Pages site, but this repository contains no implementation, tests, CI, license, or typed source of its own.

I25Q30D35
README
Unknown01mo ago

06 · Timeline

  1. Aug 7, 2024
    Joined GitHub
  2. Feb 27, 2026
    Created Polymarket_bot — Live Polymarket L2 lake + hourly shadow strategies on a small VPS. Research/learning, not live auto-trading.
  3. Apr 5, 2026
    Created Macro-Bias — Daily macro/crypto regime research app: walk-forward scores, briefings, paper paths. Learning project.
  4. Jun 1, 2026
    Created Identity — Local-first Rust context daemon: capture, memory graph, narrow clipboard context. Windows prototype.
  5. Jun 8, 2026
    Created latent-control-lab — VectorBot: route frozen LM activations to grid actions with no text generation. Toy research demo.
  6. Jun 20, 2026
    Created FiNdAlMkSkInDaL — README
  7. Jul 13, 2026
    Created tickforge — C++ limit order book + matching + simple Avellaneda-Stoikov MM. Learning project, not a trading product.
  8. Jul 13, 2026
    Created FiNdAlMkSkInDaL.github.io — Personal portfolio site
  9. Aug 13, 2026
    Created asof — Reconcile a live Polymarket order book with a Gamma warehouse snapshot
  10. Aug 18, 2026
    Most recent push to FiNdAlMkSkInDaL.github.io

07 · Compare

github.com/
FiNdAlMkSkInDaL · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total61.9
Top-end curve+5.2
Final overall67.1

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.
FiNdAlMkSkInDaL · 67.1/100 — Rate My GitHub