RRepoGEO

REPOGEO REPORT · LITE

FlashML-org/flashlib

Default branch main · commit 0eae3c92 · scanned 6/16/2026, 7:14:23 PM

GitHub: 512 stars · 38 forks

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 FlashML-org/flashlib, 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 README's first sentence to clarify purpose and differentiator

    Why:

    CURRENT
    A GPU library for classical machine-learning operators — `kmeans`, `knn`, `ivf-flat`, `pca`, `svd`, `dbscan`, `hdbscan`, `umap`, `t-sne`, regression, GEMM, and more — built on Triton and CuteDSL.
    COPY-PASTE FIX
    FlashLib is a **high-performance, memory-efficient GPU library for classical machine learning operators** like `kmeans`, `knn`, `ivf-flat`, `pca`, `svd`, `dbscan`, `hdbscan`, `umap`, `t-sne`, regression, and GEMM. Built on Triton and CuteDSL, it provides **GPU-accelerated implementations for large datasets, specifically for traditional ML, not deep learning.**
  • mediumhomepage#2
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    Add the official project homepage URL to the repository's 'About' section.

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 FlashML-org/flashlib
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
rapidsai/cuml
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. rapidsai/cuml · recommended 2×
  2. scikit-learn/scikit-learn · recommended 2×
  3. intel/scikit-learn-intelex · recommended 2×
  4. dask/dask · recommended 2×
  5. pytorch/pytorch · recommended 2×
  • CATEGORY QUERY
    How to accelerate classical machine learning algorithms on GPU for large datasets?
    you: not recommended
    AI recommended (in order):
    1. cuML (rapidsai/cuml)
    2. XGBoost (dmlc/xgboost)
    3. LightGBM (microsoft/LightGBM)
    4. CatBoost (catboost/catboost)
    5. scikit-learn (scikit-learn/scikit-learn)
    6. Intel Extension for Scikit-learn (intel/scikit-learn-intelex)
    7. Dask (dask/dask)
    8. PyTorch (pytorch/pytorch)
    9. TensorFlow (tensorflow/tensorflow)

    AI recommended 9 alternatives but never named FlashML-org/flashlib. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a high-performance Python library for GPU-accelerated clustering and dimensionality reduction.
    you: not recommended
    AI recommended (in order):
    1. cuML (rapidsai/cuml)
    2. cuDF (rapidsai/cudf)
    3. Dask (dask/dask)
    4. PyTorch (pytorch/pytorch)
    5. TensorFlow (tensorflow/tensorflow)
    6. Faiss (facebookresearch/faiss)
    7. scikit-learn (scikit-learn/scikit-learn)
    8. Intel Extension for Scikit-learn (intel/scikit-learn-intelex)
    9. Numba (numba/numba)
    10. CuPy (cupy/cupy)
    11. UMAP (lmcinnes/umap)

    AI recommended 11 alternatives but never named FlashML-org/flashlib. 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 FlashML-org/flashlib?
    pass
    AI named FlashML-org/flashlib explicitly

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

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

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

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