RRepoGEO

REPOGEO REPORT · LITE

om-ai-lab/OmAgent

Default branch main · commit c131f82b · scanned 5/9/2026, 7:37:06 PM

GitHub: 2,641 stars · 288 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 om-ai-lab/OmAgent, 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's opening paragraph to highlight multimodal orchestration

    Why:

    CURRENT
    OmAgent is python library for building multimodal language agents with ease. We try to keep the library **simple** without too much overhead like other agent framework.
    COPY-PASTE FIX
    OmAgent is a Python library designed to simplify the creation of **multimodal language agents** that can reason over text, images, video, and audio. It provides a **simple, graph-based workflow orchestration engine** to manage complex agentic tasks with minimal engineering overhead, unlike generic LLM frameworks.
  • mediumtopics#2
    Add specific topics related to agent orchestration and multi-agent systems

    Why:

    CURRENT
    agent, chatbot, gemini, gpt, gpt4, gradio, language-agent, large-language-models, llama, llava, llm, multimodal, multimodal-agent, openai, python, rag, smart-hardware, vision-and-language, vlm, workflow
    COPY-PASTE FIX
    agent, chatbot, gemini, gpt, gpt4, gradio, language-agent, large-language-models, llama, llava, llm, multimodal, multimodal-agent, multi-agent-systems, openai, orchestration, python, rag, smart-hardware, vision-and-language, vlm, workflow, workflow-engine
  • mediumcomparison#3
    Add a dedicated 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## 💡 OmAgent vs. Other Frameworks
OmAgent differentiates itself from generic LLM frameworks like LangChain and LlamaIndex by focusing on a simple, graph-based orchestration engine for building hierarchical multimodal agents with minimal engineering overhead. While other frameworks offer broad LLM integrations, OmAgent specializes in enabling complex multimodal reasoning across text, image, video, and audio inputs through its native support and streamlined workflow management.

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 om-ai-lab/OmAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 1×
  3. Microsoft Semantic Kernel · recommended 1×
  4. OpenAI Assistants API · recommended 1×
  5. Haystack · recommended 1×
  • CATEGORY QUERY
    How to build multimodal AI agents quickly with minimal engineering overhead?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Microsoft Semantic Kernel
    4. OpenAI Assistants API
    5. Haystack
    6. Gradio

    AI recommended 6 alternatives but never named om-ai-lab/OmAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Python library for developing AI agents that process text, images, video, and audio?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Hugging Face Transformers
    3. PyTorch
    4. torchvision
    5. torchaudio
    6. TensorFlow
    7. Keras
    8. TensorFlow Lite
    9. MediaPipe
    10. OpenCV
    11. Pydub

    AI recommended 11 alternatives but never named om-ai-lab/OmAgent. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 om-ai-lab/OmAgent?
    pass
    AI named om-ai-lab/OmAgent explicitly

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

  • If a team adopts om-ai-lab/OmAgent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named om-ai-lab/OmAgent 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 om-ai-lab/OmAgent solve, and who is the primary audience?
    pass
    AI named om-ai-lab/OmAgent explicitly

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

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