RRepoGEO

REPOGEO REPORT · LITE

firework8/Awesome-Skeleton-based-Action-Recognition

Default branch main · commit bd1b7a62 · scanned 6/11/2026, 5:47:51 AM

GitHub: 712 stars · 74 forks

AI VISIBILITY SCORE
22 /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
1 / 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 firework8/Awesome-Skeleton-based-Action-Recognition, 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 the README's opening to emphasize it's a curated awesome list

    Why:

    CURRENT
    We collect existing papers on skeleton-based action recognition published in prominent conferences and journals.
    COPY-PASTE FIX
    This is an awesome list collecting existing papers on skeleton-based action recognition published in prominent conferences and journals.
  • hightopics#2
    Add "awesome-list" to the repository topics

    Why:

    CURRENT
    action-recognition, papers, skeleton, skeleton-based-action-recognition
    COPY-PASTE FIX
    action-recognition, papers, skeleton, skeleton-based-action-recognition, awesome-list
  • mediumhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/firework8/Awesome-Skeleton-based-Action-Recognition

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 firework8/Awesome-Skeleton-based-Action-Recognition
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Google Scholar · recommended 1×
  3. CVF Open Access · recommended 1×
  4. ACM Digital Library · recommended 1×
  5. IEEE Xplore Digital Library · recommended 1×
  • CATEGORY QUERY
    Where can I find recent research papers on human action recognition using skeleton data?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. CVF Open Access
    4. ACM Digital Library
    5. IEEE Xplore Digital Library
    6. Semantic Scholar
    7. Microsoft Academic

    AI recommended 7 alternatives but never named firework8/Awesome-Skeleton-based-Action-Recognition. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    I need to explore the latest advancements in skeleton-based human activity understanding. Any resources?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. arXiv
    3. CVPR
    4. ICCV
    5. ECCV
    6. NeurIPS
    7. GitHub
    8. Two Minute Papers
    9. AI Coffee Break with Let's Talk AI
    10. NTU RGB+D
    11. Kinetics-Skeleton
    12. PKU-MMD

    AI recommended 12 alternatives but never named firework8/Awesome-Skeleton-based-Action-Recognition. 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 firework8/Awesome-Skeleton-based-Action-Recognition?
    pass
    AI did not name firework8/Awesome-Skeleton-based-Action-Recognition — 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 firework8/Awesome-Skeleton-based-Action-Recognition in production, what risks or prerequisites should they evaluate first?
    pass
    AI named firework8/Awesome-Skeleton-based-Action-Recognition 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 firework8/Awesome-Skeleton-based-Action-Recognition solve, and who is the primary audience?
    pass
    AI did not name firework8/Awesome-Skeleton-based-Action-Recognition — 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?

Embed your GEO score

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MARKDOWN (README)
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firework8/Awesome-Skeleton-based-Action-Recognition — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite