RRepoGEO

REPOGEO REPORT · LITE

junfanz1/Awesome-AI-Review

Default branch main · commit e7cea72d · scanned 6/1/2026, 8:57:32 AM

GitHub: 607 stars · 112 forks

AI VISIBILITY SCORE
10 /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
0 / 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 junfanz1/Awesome-AI-Review, 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
  • hightopics#1
    Add specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ai-review, ai-research, industry-insights, conference-summaries, llm-theory, agentic-ai, nvidia-gtc, deepseek, kimi
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root. For content-heavy repositories like this, consider a Creative Commons license such as CC-BY-4.0 to clarify usage rights for the reviews and insights.
  • mediumreadme#3
    Refine the README's opening description to highlight its unique focus

    Why:

    CURRENT
    Awesome AI industry & research review.
    COPY-PASTE FIX
    A curated collection of in-depth reviews and technical insights from leading AI conferences (e.g., NVIDIA GTC, Agentic AI Summit) and key research papers (e.g., LLM theory, DeepSeek, Kimi).

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 junfanz1/Awesome-AI-Review
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Papers With Code
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Papers With Code · recommended 2×
  2. arXiv.org · recommended 1×
  3. The Batch by DeepLearning.AI · recommended 1×
  4. Hugging Face Blog · recommended 1×
  5. Google AI Blog · recommended 1×
  • CATEGORY QUERY
    How can I stay updated on the latest AI research and industry developments?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Papers With Code
    3. The Batch by DeepLearning.AI
    4. Hugging Face Blog
    5. Google AI Blog
    6. Meta AI Blog
    7. Microsoft Research Blog
    8. Import AI
    9. The Neuron
    10. NeurIPS
    11. ICML
    12. CVPR
    13. ICLR
    14. ACL

    AI recommended 14 alternatives but never named junfanz1/Awesome-AI-Review. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find comprehensive reviews of LLM theory and practical applications?
    you: not recommended
    AI recommended (in order):
    1. Papers With Code
    2. arXiv
    3. Hugging Face
    4. transformers
    5. OpenAI
    6. Google AI
    7. Towards Data Science
    8. The Batch

    AI recommended 8 alternatives but never named junfanz1/Awesome-AI-Review. 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 junfanz1/Awesome-AI-Review?
    pass
    AI did not name junfanz1/Awesome-AI-Review — 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 junfanz1/Awesome-AI-Review in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name junfanz1/Awesome-AI-Review — 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?

  • In one sentence, what problem does the repo junfanz1/Awesome-AI-Review solve, and who is the primary audience?
    pass
    AI did not name junfanz1/Awesome-AI-Review — 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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junfanz1/Awesome-AI-Review — 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