RRepoGEO

REPOGEO REPORT · LITE

hyperai/awesome-ai4s

Default branch master · commit 1dc6503d · scanned 5/14/2026, 5:18:15 PM

GitHub: 3,224 stars · 505 forks

AI VISIBILITY SCORE
28 /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
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 hyperai/awesome-ai4s, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-for-science, ai4s, drug-discovery, biopharmaceutical, machine-learning, deep-learning, paper-reviews, awesome-list, research-papers, datasets, tutorials
  • highreadme#2
    Reposition the README's opening to clarify it's an 'awesome list' focused on 'AI for Science' with a strong emphasis on 'biopharmaceutical' applications

    Why:

    CURRENT
    # Awesome AI for Science
    COPY-PASTE FIX
    # Awesome AI for Science: A Curated Collection of Papers, Datasets, and Tutorials for AI in Biopharmaceutical Research and Beyond
  • mediumabout#3
    Enhance the repository description to explicitly state its nature as a curated list and its primary focus areas

    Why:

    CURRENT
    AI for Science 论文解读合集（持续更新ing），论文/数据集/教程下载：hyper.ai
    COPY-PASTE FIX
    A curated collection of AI for Science (AI4S) paper interpretations, datasets, and tutorials, with a strong focus on biopharmaceutical applications like drug discovery and development. Continuously updated. Download resources at hyper.ai.

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 hyperai/awesome-ai4s
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
REINVENT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. REINVENT · recommended 2×
  2. MolGAN · recommended 2×
  3. Open Targets Platform · recommended 1×
  4. BioBERT / SciBERT · recommended 1×
  5. IBM Watson for Genomics · recommended 1×
  • CATEGORY QUERY
    What AI methods are effective for accelerating drug discovery and development processes?
    you: not recommended
    AI recommended (in order):
    1. Open Targets Platform
    2. BioBERT / SciBERT
    3. IBM Watson for Genomics
    4. AlphaFold2
    5. REINVENT
    6. MolGAN
    7. Schrödinger
    8. DeepChem (deepchem/deepchem)
    9. KNIME Analytics Platform
    10. DrugBank
    11. BenevolentAI Platform
    12. PaccMann
    13. IQVIA AI/ML Solutions
    14. Antidote.me
    15. Unlearn.AI

    AI recommended 15 alternatives but never named hyperai/awesome-ai4s. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can machine learning models be applied to identify novel therapeutic compounds?
    you: not recommended
    AI recommended (in order):
    1. DeepChem
    2. RDKit
    3. Scikit-learn
    4. XGBoost
    5. AlphaFold
    6. RoseTTAFold
    7. AutoDock Vina
    8. GNINA
    9. REINVENT
    10. DrugEx
    11. Chemprop
    12. MolGAN
    13. GVAE

    AI recommended 13 alternatives but never named hyperai/awesome-ai4s. 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 hyperai/awesome-ai4s?
    pass
    AI named hyperai/awesome-ai4s explicitly

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

  • If a team adopts hyperai/awesome-ai4s in production, what risks or prerequisites should they evaluate first?
    pass
    AI named hyperai/awesome-ai4s 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 hyperai/awesome-ai4s solve, and who is the primary audience?
    pass
    AI did not name hyperai/awesome-ai4s — 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?

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