RRepoGEO

REPOGEO REPORT · LITE

Exorust/TorchLeet

Default branch main · commit f7765fa9 · scanned 6/25/2026, 8:48:15 AM

GitHub: 2,267 stars · 292 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface Exorust/TorchLeet, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify repo purpose and negate Rust library misidentification in README

    Why:

    COPY-PASTE FIX
    Add this sentence immediately after the existing H1: "TorchLeet is a dedicated practice resource for PyTorch skills, *not* a deep learning framework or a Rust-based library."
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    pytorch, machine-learning, ai, interview-preparation, leetcode, deep-learning, ml-engineering, coding-challenges
  • highlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root, for example, using the MIT License template, to clearly state the terms of use.

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface Exorust/TorchLeet
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Documentation
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Documentation · recommended 1×
  2. Fast.ai's 'Practical Deep Learning for Coders' · recommended 1×
  3. huggingface/transformers · recommended 1×
  4. Lightning-AI/lightning · recommended 1×
  5. Kaggle Competitions · recommended 1×
  • CATEGORY QUERY
    How can I effectively practice PyTorch skills for machine learning interview preparation?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Documentation
    2. Fast.ai's 'Practical Deep Learning for Coders'
    3. Hugging Face Transformers Library (huggingface/transformers)
    4. PyTorch Lightning (Lightning-AI/lightning)
    5. Kaggle Competitions
    6. 'Deep Learning with PyTorch' by Eli Stevens, Luca Antiga, and Thomas Viehmann
    7. LeetCode/HackerRank

    AI recommended 7 alternatives but never named Exorust/TorchLeet. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find challenging PyTorch coding problems to ace my ML engineering interviews?
    you: not recommended
    AI recommended (in order):
    1. LeetCode
    2. Kaggle
    3. XGBoost
    4. LightGBM
    5. PyTorch official tutorials
    6. PyTorch Lightning
    7. Papers With Code

    AI recommended 7 alternatives but never named Exorust/TorchLeet. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of Exorust/TorchLeet?
    pass
    AI named Exorust/TorchLeet explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts Exorust/TorchLeet in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Exorust/TorchLeet explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo Exorust/TorchLeet solve, and who is the primary audience?
    pass
    AI named Exorust/TorchLeet explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Exorust/TorchLeet — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite