RRepoGEO

REPOGEO REPORT · LITE

googlecreativelab/quickdraw-dataset

Default branch master · commit 5fe6c0a9 · scanned 5/26/2026, 5:53:01 PM

GitHub: 6,749 stars · 1,062 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 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 googlecreativelab/quickdraw-dataset, 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
  • highabout#1
    Update repository description to clarify its role

    Why:

    CURRENT
    Documentation on how to access and use the Quick, Draw! Dataset.
    COPY-PASTE FIX
    The official GitHub repository for the Quick, Draw! Dataset, a massive collection of user-drawn sketches for AI/ML research and development.
  • mediumreadme#2
    Clarify license terms in the README

    Why:

    COPY-PASTE FIX
    Ensure the 'License' section in the README clearly states the specific terms and conditions that apply to the dataset and its documentation, referencing the existing LICENSE file.
  • lowtopics#3
    Expand repository topics with relevant keywords

    Why:

    CURRENT
    dataset, quickdraw-dataset
    COPY-PASTE FIX
    dataset, quickdraw-dataset, machine-learning, ai, sketch-recognition, vector-graphics, user-generated-content

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 googlecreativelab/quickdraw-dataset
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Quick, Draw! Dataset
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Quick, Draw! Dataset · recommended 2×
  2. TU-Berlin Sketch Dataset · recommended 2×
  3. Sketchy Dataset · recommended 1×
  4. Google's Sketch Recognition Challenge Datasets · recommended 1×
  5. MNIST · recommended 1×
  • CATEGORY QUERY
    Where can I find a large collection of user-drawn sketches for AI model training?
    you: not recommended
    AI recommended (in order):
    1. Quick, Draw! Dataset
    2. Sketchy Dataset
    3. TU-Berlin Sketch Dataset
    4. Google's Sketch Recognition Challenge Datasets
    5. MNIST
    6. EMNIST
    7. Adobe's Sketch-to-Image Datasets

    AI recommended 7 alternatives but never named googlecreativelab/quickdraw-dataset. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good datasets of vector-based drawings for training a sketch recognition system?
    you: not recommended
    AI recommended (in order):
    1. Quick, Draw! Dataset
    2. Google Sketchy Dataset
    3. TU-Berlin Sketch Dataset
    4. Sketch-RNN Dataset
    5. Adobe Sketch Dataset
    6. MNIST-Sketch

    AI recommended 6 alternatives but never named googlecreativelab/quickdraw-dataset. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 googlecreativelab/quickdraw-dataset?
    pass
    AI did not name googlecreativelab/quickdraw-dataset — likely talking about a different project

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

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

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

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