RRepoGEO

REPOGEO REPORT · LITE

AIDC-AI/Marco-o1

Default branch main · commit 5f21028e · scanned 5/16/2026, 6:02:40 PM

GitHub: 1,543 stars · 81 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
35 /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
3 / 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 AIDC-AI/Marco-o1, 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
    Add specific topics to improve AI categorization

    Why:

    COPY-PASTE FIX
    llm, reasoning, agentic-ai, large-language-model, ai-agents, reinforcement-learning, optimization, real-world-solutions, planning, function-calling
  • highreadme#2
    Clarify the README's opening statement for immediate context

    Why:

    CURRENT
    🎯 **Marco-o1** not only focuses on subjects with standard answers, such as mathematics, physics, and coding that are highly suitable for the use of Reinforcement Learning, but we also emphasize some open-ended solutions. Our goal is to build a general model applicable to agentic, incorporating comprehensive planning capabilities and function call abilities.
    COPY-PASTE FIX
    🎯 **Marco-o1** is an open large reasoning model designed for real-world solutions, specifically focusing on agentic applications. It excels in comprehensive planning and function call abilities, addressing both standard answer subjects (math, physics, coding) and open-ended problems.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    [Insert the official project homepage URL here, e.g., a Hugging Face model page or project website]

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 AIDC-AI/Marco-o1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Llama 3
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Llama 3 · recommended 2×
  2. Mixtral 8x7B · recommended 1×
  3. Qwen 1.5 · recommended 1×
  4. CodeLlama · recommended 1×
  5. Gemma · recommended 1×
  • CATEGORY QUERY
    Need an open large reasoning model for agentic applications with strong planning capabilities.
    you: not recommended
    AI recommended (in order):
    1. Llama 3
    2. Mixtral 8x7B
    3. Qwen 1.5
    4. CodeLlama
    5. Gemma

    AI recommended 5 alternatives but never named AIDC-AI/Marco-o1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are robust large models for complex real-world problem-solving across various subjects?
    you: not recommended
    AI recommended (in order):
    1. GPT-4
    2. Claude 3 Opus
    3. Gemini 1.5 Pro
    4. Llama 3
    5. Mistral Large
    6. Cohere Command R+

    AI recommended 6 alternatives but never named AIDC-AI/Marco-o1. 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 AIDC-AI/Marco-o1?
    pass
    AI named AIDC-AI/Marco-o1 explicitly

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

  • If a team adopts AIDC-AI/Marco-o1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AIDC-AI/Marco-o1 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 AIDC-AI/Marco-o1 solve, and who is the primary audience?
    pass
    AI named AIDC-AI/Marco-o1 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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AIDC-AI/Marco-o1 — 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