RRepoGEO

REPOGEO REPORT · LITE

Technion-Kishony-lab/data-to-paper

Default branch main · commit 81df14c4 · scanned 5/29/2026, 5:28:26 PM

GitHub: 799 stars · 93 forks

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 Technion-Kishony-lab/data-to-paper, 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
    Reposition README's opening to emphasize full scientific paper generation

    Why:

    CURRENT
    ## Backward-traceable AI-driven Research
    COPY-PASTE FIX
    ## data-to-paper: AI-Driven Generation of Backward-Traceable Scientific Papers from Raw Data
  • hightopics#2
    Add specific topics to improve category visibility

    Why:

    CURRENT
    agents, ai, autonomous-agents, interactive-machine-learning, llm, scientific-research
    COPY-PASTE FIX
    agents, ai, autonomous-agents, interactive-machine-learning, llm, scientific-research, scientific-publishing, research-automation, data-to-paper, paper-generation, traceable-ai, verifiable-research
  • mediumcomparison#3
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Unlike general workflow tools (e.g., Nextflow, Snakemake) or broad AI platforms (e.g., ChatGPT, Elicit), data-to-paper uniquely focuses on generating a **complete, end-to-end scientific paper draft**—including methods, results, discussion, and abstract—directly from raw data, ensuring full backward traceability.

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 Technion-Kishony-lab/data-to-paper
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ChatGPT
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ChatGPT · recommended 2×
  2. Nextflow · recommended 1×
  3. Snakemake · recommended 1×
  4. Jupyter Notebooks · recommended 1×
  5. JupyterLab · recommended 1×
  • CATEGORY QUERY
    How can I automate the entire scientific research process from data to paper?
    you: not recommended
    AI recommended (in order):
    1. Nextflow
    2. Snakemake
    3. Jupyter Notebooks
    4. JupyterLab
    5. Papermill
    6. R Markdown
    7. Quarto
    8. GitHub Actions
    9. GitLab CI/CD
    10. Pandoc
    11. Zotero
    12. Mendeley
    13. ChatGPT
    14. GPT-4

    AI recommended 14 alternatives but never named Technion-Kishony-lab/data-to-paper. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for AI agents to generate traceable, verifiable scientific papers from raw data.
    you: not recommended
    AI recommended (in order):
    1. Elicit
    2. Semantic Scholar AI
    3. ChatGPT
    4. spaCy
    5. NLTK
    6. Hugging Face Transformers

    AI recommended 6 alternatives but never named Technion-Kishony-lab/data-to-paper. 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 Technion-Kishony-lab/data-to-paper?
    pass
    AI named Technion-Kishony-lab/data-to-paper explicitly

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

  • If a team adopts Technion-Kishony-lab/data-to-paper in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Technion-Kishony-lab/data-to-paper 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 Technion-Kishony-lab/data-to-paper solve, and who is the primary audience?
    pass
    AI named Technion-Kishony-lab/data-to-paper explicitly

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

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