RRepoGEO

REPOGEO REPORT · LITE

diasks2/ruby-nlp

Default branch master · commit fbe3b867 · scanned 5/20/2026, 6:43:32 AM

GitHub: 1,284 stars · 106 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
57 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
Rule findings
1 pass · 0 warn · 1 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 diasks2/ruby-nlp, 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
    Clarify README's opening to explicitly state it's an "awesome list"

    Why:

    CURRENT
    Ruby Natural Language Processing Resources
A collection of Natural Language Processing (NLP) Ruby libraries, tools and software.
    COPY-PASTE FIX
    Awesome Ruby Natural Language Processing Resources
A curated collection of Ruby NLP libraries, tools, and software, designed to help developers find the right resources for their projects.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ruby, nlp, natural-language-processing, awesome-list, awesome, collection, libraries, tools, software, machine-learning
  • highlicense#3
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) in the repository root to clearly state the terms under which the collection is provided.

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
1 / 2
50% of queries surface diasks2/ruby-nlp
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
ruby-nlp/ruby-nlp
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ruby-nlp/ruby-nlp · recommended 1×
  2. louismullie/stanford-core-nlp · recommended 1×
  3. treat/treat · recommended 1×
  4. diasks2/pragmatic_segmenter · recommended 1×
  5. aurelian/fast-stemmer · recommended 1×
  • CATEGORY QUERY
    What are the best natural language processing libraries available for Ruby development?
    you: not recommended
    AI recommended (in order):
    1. Ruby/NLP (ruby-nlp/ruby-nlp)
    2. stanford-core-nlp (louismullie/stanford-core-nlp)
    3. Treat (treat/treat)
    4. pragmatic_segmenter (diasks2/pragmatic_segmenter)
    5. fast_stemmer (aurelian/fast-stemmer)
    6. classifier-reborn (jekyll/classifier-reborn)

    AI recommended 6 alternatives but never named diasks2/ruby-nlp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find a comprehensive list of Ruby tools for various NLP tasks?
    you: #1
    AI recommended (in order):
    1. ruby-nlp ← you
    2. stanford-core-nlp
    3. pragmatic_segmenter
    4. treat
    5. natto
    6. fast_stemmer
    7. classifier-reborn
    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 diasks2/ruby-nlp?
    pass
    AI named diasks2/ruby-nlp explicitly

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

  • If a team adopts diasks2/ruby-nlp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named diasks2/ruby-nlp 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 diasks2/ruby-nlp solve, and who is the primary audience?
    pass
    AI did not name diasks2/ruby-nlp — 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite