RRepoGEO

REPOGEO REPORT · LITE

vifreefly/kimuraframework

Default branch master · commit 6f4fd43a · scanned 5/22/2026, 10:52:59 PM

GitHub: 1,100 stars · 163 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
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 vifreefly/kimuraframework, 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
  • highabout#1
    Clarify the Description to emphasize 'Ruby framework'

    Why:

    CURRENT
    Write web scrapers in Ruby using a clean, AI-assisted DSL. Kimurai uses AI to figure out where the data lives, then caches the selectors and scrapes with pure Ruby. Get the intelligence of an LLM without the per-request latency or token costs.
    COPY-PASTE FIX
    Kimurai is an AI-assisted web scraping framework for Ruby. It uses AI to automatically detect data selectors, then caches them for efficient, pure Ruby scraping without per-request LLM costs.
  • mediumreadme#2
    Add a sentence to the README explicitly stating how Kimurai solves the selector problem

    Why:

    COPY-PASTE FIX
    Unlike traditional scrapers that require manual XPath or CSS selector management, Kimurai's AI automatically identifies and caches data locations, significantly reducing development and maintenance effort.
  • lowtopics#3
    Add AI/LLM-specific topics

    Why:

    CURRENT
    antidetect-browser, camoufox, crawler, headless-chrome, kimurai, ruby, scraper, scrapy, web-scraping
    COPY-PASTE FIX
    antidetect-browser, ai-powered, camoufox, crawler, generative-ai, headless-chrome, kimurai, llm, ruby, scraper, scrapy, web-scraping

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 vifreefly/kimuraframework
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Nokogiri
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Nokogiri · recommended 2×
  2. Mechanize · recommended 2×
  3. OpenURI · recommended 1×
  4. HTTParty · recommended 1×
  5. Watir · recommended 1×
  • CATEGORY QUERY
    How to build intelligent web scrapers in Ruby without high LLM costs?
    you: not recommended
    AI recommended (in order):
    1. Nokogiri
    2. OpenURI
    3. HTTParty
    4. Mechanize
    5. Watir
    6. Selenium WebDriver
    7. selenium-webdriver gem
    8. Scrubyt
    9. Pry
    10. anemone

    AI recommended 10 alternatives but never named vifreefly/kimuraframework. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What's a good Ruby framework for robust web scraping with automatic selector detection?
    you: not recommended
    AI recommended (in order):
    1. ScrapingBee
    2. Ferrum
    3. Capybara
    4. Mechanize
    5. Nokogiri

    AI recommended 5 alternatives but never named vifreefly/kimuraframework. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 vifreefly/kimuraframework?
    pass
    AI did not name vifreefly/kimuraframework — 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?

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