01 · Roasts
Product shelf, no checkout line
You have named products from LeetPush to Mūlpath, but the portfolio has 1 total star and 0 forks.
CI is the missing teammate
Every scored repository lacks CI, including LeetPush and Mūlpath—the two repos already closest to production discipline.
Credential speedrun
Portfolio embeds Supabase service/database credentials in source; rotating those keys should outrank another visual polish pass.
Scaffold cemetery
AI_Agent and Elite-Store are both empty repositories, adding more tombstones than shipping evidence.
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% weight56D
- Consistency20% weight60C
- Quality20% weight65C
- Depth15% weight55D
- Breadth10% weight55D
- Community10% weight25F
03 · Stats
365-day commit heatmap
34 active days
Language distribution
- JavaScript91%
- TypeScript6%
- HTML2%
- CSS0%
- Java0%
- MDX0%
- Other1%
04 · Numbers
Owned repos
non-fork
23
Commits
last 12 months
211
Followers
3
Joined GitHub
Aug 2024
05 · Top repos
Iamudt19 /
mulpath
Substantial documented full-stack Ayurvedic traceability platform spanning React, Express/Prisma, Solidity contracts, offline plant analysis, and consumer verification, but with no stars, license, CI, or evidence of external adoption.
Iamudt19 /
Chaptr
Chaptr is a substantial typed Next.js/Supabase relationship journal with AI-assisted trait extraction, pattern detection, trust scoring, and judgement workflows, but it has no visible adoption, tests, CI, or license.
Iamudt19 /
LeetPush
A documented TypeScript MV3 Chrome extension with GitHub sync, LeetCode detection, retry queue, dashboard, and focused Vitest coverage, but only 1 star and no CI or demonstrated external adoption.
Iamudt19 /
Secuscan
A substantial early-stage Vulta security-scanning SaaS with Express/React layers, SSRF defenses, secret and dependency adapters, project auth, and CI-facing scan APIs, but no documented adoption or validation infrastructure.
Iamudt19 /
quickpad
QuickPad is a polished single-file HTML shared-notepad interface with theme switching, URL sharing, Firebase/Vercel hosting configuration, and SEO artifacts, but has no documented adoption, tests, CI, license, or typed code.
Iamudt19 /
Leetcode-Questions
A small, documented Java LeetCode solution repository with three indexed problems and per-solution READMEs, but no tests, CI, license, or evidence of external adoption.
Iamudt19 /
Portfolio
A substantial static Framer-export portfolio with custom interactive canvas/UI work and serverless Supabase persistence, but weakened by exposed credentials, duplicated backend paths, no tests/CI, and no license.
Iamudt19 /
AI_Agent
Empty repository with no files, metadata, documentation, or observable implementation; it appears to be an unstarted scaffold.
Iamudt19 /
Elite-Store
Empty repository with no source files, documentation, metadata, or recorded development activity.
06 · Timeline
- Aug 15, 2024Joined GitHub
- May 26, 2026Created Chaptr
- May 28, 2026Created Portfolio
- Jun 1, 2026Created quickpad
- Jul 18, 2026Created Elite-Store
- Aug 2, 2026Created Secuscan
- Aug 15, 2026Created mulpath
- Sep 9, 2026Created AI_Agent
- Sep 12, 2026Created Leetcode-Questions
- Sep 12, 2026Created LeetPush — Leetcode to Github direct commit
- Sep 12, 2026Most recent push to LeetPush
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.