RRepoGEO

REPOGEO REPORT · LITE

om-ai-lab/OmAgent

Default branch main · commit c131f82b · scanned 6/19/2026, 5:02:43 PM

GitHub: 2,660 stars · 289 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)

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

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 introduction to clarify OmAgent's role as a framework

    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 framework for building multimodal language agents with ease, simplifying the complex orchestration of various inputs (text, image, video, audio) and models. It provides a flexible architecture for fast prototyping and production of advanced agent systems, differentiating it from raw APIs or single-modal tools.
  • mediumtopics#2
    Add more specific topics to highlight framework and orchestration capabilities

    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, openai, python, rag, smart-hardware, vision-and-language, vlm, workflow, agent-framework, agent-orchestration, multi-agent-systems
  • lowabout#3
    Refine the 'About' description to emphasize 'framework' and 'simplification'

    Why:

    CURRENT
    [EMNLP-2024] Build multimodal language agents for fast prototype and production
    COPY-PASTE FIX
    [EMNLP-2024] A Python framework to simplify building, deploying, and managing multimodal language agents for fast prototype and production.

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
OpenAI API
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI API · recommended 2×
  2. LangChain · recommended 1×
  3. LlamaIndex · recommended 1×
  4. Haystack · recommended 1×
  5. Hugging Face Transformers · recommended 1×
  • CATEGORY QUERY
    How to build multimodal AI agents easily in Python for various inputs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. OpenAI API
    5. Hugging Face Transformers
    6. Microsoft Semantic Kernel

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

    Show full AI answer
  • CATEGORY QUERY
    Frameworks for developing AI agents that reason across text, image, video, and audio?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. DALL-E 3
    3. Stable Diffusion
    4. OpenAI Whisper
    5. LlamaIndex (run-llama/llama_index)
    6. Hugging Face Transformers (huggingface/transformers)
    7. Diffusers (huggingface/diffusers)
    8. OpenAI API
    9. GPT-4V
    10. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    11. Azure AI Vision
    12. Azure AI Speech

    AI recommended 12 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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om-ai-lab/OmAgent — 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