RRepoGEO

REPOGEO REPORT · LITE

ai4co/awesome-fm4co

Default branch main · commit cba53132 · scanned 6/5/2026, 4:38:40 PM

GitHub: 541 stars · 42 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 ai4co/awesome-fm4co, 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
    Reposition the README H1 to specify it's an "Awesome List" of "Research Papers"

    Why:

    CURRENT
    <h1 align="center">Foundation Models for Combinatorial Optimization</h1>
    COPY-PASTE FIX
    <h1 align="center">Awesome List: Foundation Models for Combinatorial Optimization Research Papers</h1>
  • mediumhomepage#2
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/ai4co/awesome-fm4co
  • lowtopics#3
    Add more specific topics to reinforce the content type

    Why:

    CURRENT
    awesome, awesome-list, combinatorial-optimization, foundation-models, lists, machine-learning, neural-combinatorial-optimization
    COPY-PASTE FIX
    awesome, awesome-list, combinatorial-optimization, foundation-models, lists, machine-learning, neural-combinatorial-optimization, research-papers, literature-review

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 ai4co/awesome-fm4co
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ChatGPT
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. ChatGPT · recommended 1×
  2. Claude · recommended 1×
  3. Google Gemini · recommended 1×
  4. GitHub Copilot · recommended 1×
  5. Code Llama · recommended 1×
  • CATEGORY QUERY
    How can I leverage large language models to solve combinatorial optimization problems?
    you: not recommended
    AI recommended (in order):
    1. ChatGPT
    2. Claude
    3. Google Gemini
    4. GitHub Copilot
    5. Code Llama
    6. LangChain (langchain-ai/langchain)
    7. LlamaIndex (run-llama/llama_index)

    AI recommended 7 alternatives but never named ai4co/awesome-fm4co. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find recent research on applying foundation models to combinatorial optimization tasks?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. NeurIPS
    4. ICLR
    5. AAAI
    6. IJCAI
    7. Operations Research
    8. Management Science

    AI recommended 8 alternatives but never named ai4co/awesome-fm4co. 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 ai4co/awesome-fm4co?
    pass
    AI did not name ai4co/awesome-fm4co — 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 ai4co/awesome-fm4co in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ai4co/awesome-fm4co 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 ai4co/awesome-fm4co solve, and who is the primary audience?
    pass
    AI named ai4co/awesome-fm4co explicitly

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

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ai4co/awesome-fm4co — 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