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#98 — Top 94.4%

Cameloo1

Wasif Amin

B

Solid engineer

Overall

0.0

/ 100

01 · Roasts

Factory, not fandom

28 public repos and 147 recent sampled commits, yet the portfolio has 3 total stars and 0 forks.

Tests where it counts

DFRI, dbn-bookcheck, codegraph-mcp, and relaybase are serious about CI; siem-lab is still an Elastic Stack showroom with empty rooms.

Rust gravity well

Rust is 43% of the profile, and the 10-crate codegraph-mcp workspace makes that dominance look intentional.

Thesis has not compiled

scaleless calls itself pre-implementation: no executable code, tests, CI, license, or gitignore yet.

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
    82A
  • Depth
    15% weight
    60C
  • Breadth
    10% weight
    95S
  • Community
    10% weight
    30F

03 · Stats

365-day commit heatmap

89 active days

Less
More

Language distribution

7 langs
  • Rust43%
  • TypeScript16%
  • Python12%
  • Go8%
  • JavaScript7%
  • Shell5%
  • Other9%

04 · Numbers

Owned repos

non-fork

28

Commits

last 12 months

387

Followers

5

Joined GitHub

Oct 2023

05 · Top repos

Cameloo1 /

dbn-bookcheck

67/100

A rigorously engineered Rust/Node market-data toolkit with strict DBN decoding, order-book reconstruction, MBP-10 validation, sweep detection, benchmarks, and a tested static case study; adoption is currently limited despite a deployed GitHub Pages artifact.

I35Q85D50
READMETestsCITyped
Rust01mo ago

Cameloo1 /

dfri

63/100

DFRI is a substantial, documented Python data product with a deployed scoreboard, statistical nowcasts, provenance-aware attribution, immutable ledgers, reproducible publication, tests, and CI, but currently has 0 stars and no demonstrated external adoption.

I35Q78D55
READMETestsCI
Python0this week

Cameloo1 /

codegraph-mcp

58/100

A substantial Rust workspace for proof-oriented code intelligence, with 10 crates, SQLite-backed graph/query layers, MCP and CLI surfaces, extensive docs, tests, and cross-platform CI; adoption remains minimal at 1 star.

I20Q78D58
READMETestsCITyped
Rust11mo ago

Cameloo1 /

relaybase

58/100

A substantial, well-engineered TypeScript/Go local development control plane with MCP, agent approvals, routing, lifecycle verification, and a broad cross-platform CI/test system, but currently has no demonstrated adoption.

I20Q82D60
READMETestsCITyped
TypeScript01mo ago

Cameloo1 /

free-inference-autoscaler

57/100

A carefully engineered, typed TypeScript admission-control library for zero-cost LLM routes, with strong safety boundaries, persistence, quota governance, extensive tests, and documentation, but no demonstrated adoption or sustained history.

I22Q76D20
READMETestsTyped
TypeScript01mo ago

Cameloo1 /

conversational-notifications

48/100

A substantial, security-conscious Windows notification system with a shipping PowerShell notifier and a release-gated conversational controller, backed by durable state, authenticated IPC, provider guards, and extensive tests, but with no demonstrated adoption yet.

I20Q68D55
READMETests
JavaScript01mo ago

Cameloo1 /

agent-friendly

41/100

A well-documented, security-conscious MCP gateway for Cloudflare’s agent-readiness scanner, with strong offline tests and cross-platform CI, but currently a one-day, zero-star project with no demonstrated external adoption.

I20Q72D20
READMETestsCI
JavaScript01mo ago

Cameloo1 /

cameloo1

37/100

A small personal GitHub profile repo that pairs a scheduled Python-generated /ES market ticker with a polished README, but has no tests, license, typing, or demonstrated adoption.

I25Q35D50
READMECI
Python0this week

Cameloo1 /

siem-lab

27/100

Documented but largely scaffolded local SIEM lab: Terraform creates Elasticsearch, Logstash, and Kibana containers, while ingestion, detections, dashboards, tests, and CI remain unimplemented.

I20Q38D25
README
HTML01mo ago

Cameloo1 /

scaleless

15/100

scaleless is a clearly articulated infrastructure-safety thesis, but explicitly remains pre-implementation with no executable code, tests, CI, or demonstrated adoption.

I15Q25D5
README
Unknown01mo ago

06 · Timeline

  1. Oct 11, 2023
    Joined GitHub
  2. Aug 7, 2025
    Created siem-lab
  3. May 6, 2026
    Created relaybase — Manage multiple local dev servers from one place. Includes a dedicated lightweight agent and MCP controls for AI agents
  4. May 8, 2026
    Created codegraph-mcp — Local repo intelligence layer for AI coding agents. Indexes code into typed graphs, returns proof-labeled context packets, keeps changed files fresh, and validates edits with linte
  5. May 15, 2026
    Created scaleless
  6. May 20, 2026
    Created cameloo1
  7. Jul 19, 2026
    Created conversational-notifications — Get conversational status updates on agent activity — and talk back. On-device TTS announces, you reply by voice, and a dedicated agent answers with real thread, log, and repo cont
  8. Jul 31, 2026
    Created dbn-bookcheck — Reconstruct the ES order book from DBN market-by-order data and prove it against the exchange's own MBP-10 feed.
  9. Aug 4, 2026
    Created agent-friendly — A dedicated agent-readiness SEO scanner for your website. Wraps Cloudflare's isitagentready into an on-device MCP.
  10. Aug 4, 2026
    Created dfri — DFRI estimates the share of covered companies' U.S. consumer revenue funded by new consumer credit. It also predicts each month's change in U.S. consumer borrowing before the Feder
  11. Aug 8, 2026
    Created free-inference-autoscaler — Lets you use free models from OpenRouter and NVIDIA. Checks a route is actually free before each call, keeps background jobs from eating the quota your users need, and backs off wh
  12. Sep 18, 2026
    Most recent push to cameloo1

07 · Compare

github.com/
Cameloo1 · 6dmedian coder

08 · Rubric

How this score was produced

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

CategoryWeightScoreContrib.
Raw total66.4
Top-end curve+5.8
Final overall72.2

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.
Cameloo1 · 72.2/100 — Rate My GitHub