RRepoGEO

REPOGEO REPORT · LITE

JohnSnowLabs/nlu

Default branch master · commit 0513a773 · scanned 6/1/2026, 4:26:58 PM

GitHub: 963 stars · 139 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 JohnSnowLabs/nlu, 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 H1 and opening sentence for better category recall

    Why:

    CURRENT
    # NLU: The Power of Spark NLP, the Simplicity of Python
John Snow Labs' NLU is a Python library for applying state-of-the-art text mining, directly on any dataframe, with a single line of code.
    COPY-PASTE FIX
    # John Snow Labs NLU: State-of-the-Art NLP for Dataframes in a Single Line of Python
John Snow Labs' NLU is the fastest and most accurate Python library for applying thousands of production-grade, state-of-the-art NLP models directly on any dataframe, with unparalleled simplicity.
  • mediumhomepage#2
    Add the official homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://nlu.johnsnowlabs.com/
  • lowlicense#3
    Clarify the repository's license(s) directly in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under [describe the actual license(s) here, e.g., "a custom license combining elements of X and Y" or "the specific terms outlined in the LICENSE file"]. Please refer to the [LICENSE](LICENSE) file for full details.

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 JohnSnowLabs/nlu
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. spaCy · recommended 2×
  3. Flair · recommended 2×
  4. Gensim · recommended 2×
  5. TextBlob · recommended 1×
  • CATEGORY QUERY
    How to apply advanced NLP techniques to dataframes using a single line of Python?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. Flair
    4. TextBlob
    5. Gensim

    AI recommended 5 alternatives but never named JohnSnowLabs/nlu. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What robust Python library provides many state-of-the-art NLP models for production use?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. spaCy
    3. Flair
    4. AllenNLP
    5. NLTK
    6. Gensim

    AI recommended 6 alternatives but never named JohnSnowLabs/nlu. 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 JohnSnowLabs/nlu?
    pass
    AI named JohnSnowLabs/nlu explicitly

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

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

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

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JohnSnowLabs/nlu — 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