RRepoGEO

REPOGEO REPORT · LITE

SakanaAI/AI-Scientist-v2

Default branch main · commit 96bd5161 · scanned 5/23/2026, 12:52:43 AM

GitHub: 6,350 stars · 857 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 SakanaAI/AI-Scientist-v2, 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
  • mediumreadme#1
    Clarify the repository's license in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, e.g., "## License\nThis project is licensed under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details regarding usage and distribution."
  • lowhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://sakana.ai/ai-scientist-first-publication/

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 SakanaAI/AI-Scientist-v2
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
GPT-4
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. GPT-4 · recommended 2×
  2. AlphaFold · recommended 2×
  3. Google Cloud AutoML · recommended 2×
  4. Claude 3 · recommended 1×
  5. Gemini Advanced · recommended 1×
  • CATEGORY QUERY
    How can I automate hypothesis generation and experimental design for scientific research?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3
    3. Gemini Advanced
    4. AlphaFold
    5. RoseTTAFold
    6. OpenAI Gym (openai/gym)
    7. Stable Baselines3 (DLR-RM/stable-baselines3)
    8. ChemAxon
    9. RDKit (rdkit/rdkit)
    10. Google Cloud AutoML
    11. H2O.ai
    12. TPOT (EpistasisLab/tpot)
    13. Jupyter Notebooks (jupyter/notebook)
    14. NumPy (numpy/numpy)
    15. SciPy (scipy/scipy)
    16. Pandas (pandas-dev/pandas)
    17. scikit-learn (scikit-learn/scikit-learn)
    18. Matplotlib (matplotlib/matplotlib)
    19. Opentrons (Opentrons/opentrons)
    20. Tecan
    21. Hamilton

    AI recommended 21 alternatives but never named SakanaAI/AI-Scientist-v2. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What AI tools exist for autonomous scientific research, including data analysis and paper writing?
    you: not recommended
    AI recommended (in order):
    1. Elicit
    2. Semantic Scholar
    3. ChatGPT
    4. GPT-4
    5. Claude
    6. Gemini
    7. AlphaFold
    8. ChemGPT
    9. BioGPT
    10. Google Cloud AutoML
    11. H2O.ai Driverless AI
    12. Scite.ai

    AI recommended 12 alternatives but never named SakanaAI/AI-Scientist-v2. 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 SakanaAI/AI-Scientist-v2?
    pass
    AI named SakanaAI/AI-Scientist-v2 explicitly

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

  • If a team adopts SakanaAI/AI-Scientist-v2 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named SakanaAI/AI-Scientist-v2 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 SakanaAI/AI-Scientist-v2 solve, and who is the primary audience?
    pass
    AI named SakanaAI/AI-Scientist-v2 explicitly

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

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SakanaAI/AI-Scientist-v2 — 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