RRepoGEO

REPOGEO REPORT · LITE

garylab/MakeMoneyWithAI

Default branch main · commit f0b8355c · scanned 6/27/2026, 11:47:44 PM

GitHub: 513 stars · 100 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 garylab/MakeMoneyWithAI, 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 sentence to emphasize it's a guide/list of strategies

    Why:

    CURRENT
    Make Money With AI is a curated list of AI tools and projects that help you turn open-source into income.
    COPY-PASTE FIX
    Make Money With AI is a comprehensive, community-curated guide and list of open-source AI projects and strategies designed to help you generate income and build commercial applications.
  • highlicense#2
    Add a LICENSE file to clarify usage rights for the list content

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository with the MIT License text.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add a URL to the repository's About section. Consider creating a simple GitHub Pages site for the project or linking to a relevant community forum or blog post that expands on the project's mission.

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 garylab/MakeMoneyWithAI
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. PyTorch · recommended 1×
  3. TensorFlow · recommended 1×
  4. scikit-learn · recommended 1×
  5. OpenCV · recommended 1×
  • CATEGORY QUERY
    What open-source AI tools can I use to build monetizable services?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PyTorch
    3. TensorFlow
    4. scikit-learn
    5. OpenCV
    6. Gradio
    7. Streamlit
    8. Faiss

    AI recommended 8 alternatives but never named garylab/MakeMoneyWithAI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I leverage open-source AI agents and LLMs for commercial applications?
    you: not recommended
    AI recommended (in order):
    1. Llama 2
    2. LangChain
    3. LlamaIndex
    4. Mistral 7B
    5. Mixtral 8x7B
    6. Hugging Face Transformers Library
    7. AutoGen
    8. CrewAI
    9. Falcon 40B
    10. Falcon 180B
    11. Ollama
    12. LM Studio

    AI recommended 12 alternatives but never named garylab/MakeMoneyWithAI. 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 garylab/MakeMoneyWithAI?
    pass
    AI named garylab/MakeMoneyWithAI explicitly

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

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