RRepoGEO

REPOGEO REPORT · LITE

prescience-data/dark-knowledge

Default branch main · commit 0fa81a44 · scanned 6/16/2026, 5:42:46 PM

GitHub: 752 stars · 45 forks

AI VISIBILITY SCORE
28 /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
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 prescience-data/dark-knowledge, 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 repo's purpose in README's opening

    Why:

    CURRENT
    # Dark Knowledge
    COPY-PASTE FIX
    # Dark Knowledge: A Curated Library of Research Papers on Counter-Detection and Web Privacy
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) in the repository root.
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    Add a relevant URL (e.g., a project website, a related organization page, or even the GitHub repo URL itself) to the 'Homepage' field in the repository settings.

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 prescience-data/dark-knowledge
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Scholar
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Scholar · recommended 1×
  2. ACM Digital Library · recommended 1×
  3. IEEE Xplore Digital Library · recommended 1×
  4. arXiv · recommended 1×
  5. ResearchGate · recommended 1×
  • CATEGORY QUERY
    Where can I find research papers on browser fingerprinting techniques and counter-detection?
    you: not recommended
    AI recommended (in order):
    1. Google Scholar
    2. ACM Digital Library
    3. IEEE Xplore Digital Library
    4. arXiv
    5. ResearchGate
    6. Academia.edu
    7. USENIX Security Symposium Proceedings
    8. NDSS Symposium Proceedings

    AI recommended 8 alternatives but never named prescience-data/dark-knowledge. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for web scraping without triggering bot detection systems?
    you: not recommended
    AI recommended (in order):
    1. fake_useragent
    2. time
    3. Bright Data
    4. Oxylabs
    5. ScrapingBee
    6. 2Captcha
    7. Anti-Captcha
    8. requests
    9. robotparser
    10. Puppeteer
    11. Selenium

    AI recommended 11 alternatives but never named prescience-data/dark-knowledge. 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 prescience-data/dark-knowledge?
    pass
    AI did not name prescience-data/dark-knowledge — 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 prescience-data/dark-knowledge in production, what risks or prerequisites should they evaluate first?
    pass
    AI named prescience-data/dark-knowledge 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 prescience-data/dark-knowledge solve, and who is the primary audience?
    pass
    AI named prescience-data/dark-knowledge explicitly

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

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MARKDOWN (README)
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