RRepoGEO

REPOGEO REPORT · LITE

worldcoin/awesome-zkml

Default branch main · commit 106e5ea1 · scanned 5/28/2026, 7:33:07 PM

GitHub: 1,048 stars · 214 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 worldcoin/awesome-zkml, 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
  • hightopics#1
    Update repository topics to reflect content

    Why:

    CURRENT
    managed-by-terraform, team-crypto
    COPY-PASTE FIX
    awesome-list, zero-knowledge, machine-learning, zkml, cryptography, verifiable-computation, ai-models, resources
  • highreadme#2
    Reposition the README H1 and opening paragraph to clarify purpose

    Why:

    CURRENT
    # awesome-zkml

A place where you can find content, codebases, scientific papers, projects and applications related to ZKML.
    COPY-PASTE FIX
    # awesome-zkml: A Curated List of Zero-Knowledge Machine Learning Resources

This repository is the definitive awesome list for Zero-Knowledge Machine Learning (ZKML), providing a comprehensive collection of content, codebases, scientific papers, projects, and applications related to this emerging field.
  • mediumabout#3
    Update the repository description

    Why:

    CURRENT
    awesome-zkml repository
    COPY-PASTE FIX
    A comprehensive, curated awesome list of resources for Zero-Knowledge Machine Learning (ZKML), including papers, codebases, projects, and applications.

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 worldcoin/awesome-zkml
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mina Protocol
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mina Protocol · recommended 2×
  2. RISC Zero · recommended 2×
  3. ZKML.org · recommended 1×
  4. Awesome ZKML · recommended 1×
  5. a16z Crypto · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of resources to learn about zero-knowledge machine learning?
    you: not recommended
    AI recommended (in order):
    1. ZKML.org
    2. Awesome ZKML
    3. a16z Crypto
    4. ZKProof.org
    5. Mina Protocol
    6. SnarkyJS
    7. RISC Zero
    8. Ezkl

    AI recommended 8 alternatives but never named worldcoin/awesome-zkml. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading projects and applications exploring verifiable computation for AI models?
    you: not recommended
    AI recommended (in order):
    1. EZKL
    2. Orion
    3. Giza
    4. Modulus Labs
    5. RISC Zero
    6. Mina Protocol
    7. Aleo

    AI recommended 7 alternatives but never named worldcoin/awesome-zkml. 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 worldcoin/awesome-zkml?
    pass
    AI did not name worldcoin/awesome-zkml — 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 worldcoin/awesome-zkml in production, what risks or prerequisites should they evaluate first?
    pass
    AI named worldcoin/awesome-zkml 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 worldcoin/awesome-zkml solve, and who is the primary audience?
    pass
    AI named worldcoin/awesome-zkml explicitly

    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
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