RRepoGEO

REPOGEO REPORT · LITE

openai/grok

Default branch main · commit 3d64b1d8 · scanned 6/29/2026, 12:17:58 PM

GitHub: 4,250 stars · 585 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)

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

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 openai/grok, 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

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

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 to clarify the repo's identity

    Why:

    CURRENT
    # OpenAI Grok Curve Experiments
    COPY-PASTE FIX
    # Code for the 'Grokking' Generalization Paper
  • highabout#2
    Add a concise description to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    Code accompanying the paper 'Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets', exploring the phenomenon of grokking in neural networks.

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 openai/grok
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ImageDataGenerator
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ImageDataGenerator · recommended 1×
  2. Augly · recommended 1×
  3. nlpaug · recommended 1×
  4. TextAttack · recommended 1×
  5. ResNet · recommended 1×
  • CATEGORY QUERY
    How can I improve machine learning model generalization on limited training data?
    you: not recommended
    AI recommended (in order):
    1. ImageDataGenerator
    2. Augly
    3. nlpaug
    4. TextAttack
    5. ResNet
    6. VGG
    7. BERT
    8. GPT-3
    9. Hugging Face Transformers
    10. TensorFlow Hub
    11. PyTorch Hub
    12. Dropout
    13. Early Stopping
    14. Random Forest
    15. XGBoost
    16. LightGBM
    17. CatBoost
    18. Bagging
    19. LogisticRegression
    20. LinearRegression
    21. SVC
    22. SVR
    23. Generative Adversarial Networks (GANs)
    24. StyleGAN
    25. SMOTE
    26. KFold

    AI recommended 26 alternatives but never named openai/grok. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks exist for exploring generalization in neural networks on algorithmic tasks?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. TensorFlow
    3. Keras API
    4. JAX
    5. Flax
    6. Haiku
    7. dm_env
    8. acme
    9. CLRS
    10. Neural Algorithmic Learner Libraries
    11. PyTorch Geometric (PyG)
    12. Deep Graph Library (DGL)

    AI recommended 12 alternatives but never named openai/grok. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 openai/grok?
    pass
    AI named openai/grok explicitly

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

  • If a team adopts openai/grok in production, what risks or prerequisites should they evaluate first?
    pass
    AI named openai/grok 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 openai/grok solve, and who is the primary audience?
    pass
    AI named openai/grok explicitly

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

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openai/grok — 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
openai/grok — RepoGEO report