RRepoGEO

REPOGEO REPORT · LITE

omnigent-ai/omnigent

Default branch main · commit c00bbc52 · scanned 6/16/2026, 2:27:11 PM

GitHub: 2,354 stars · 285 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 omnigent-ai/omnigent, 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
  • highabout#1
    Reposition the About section description to highlight unique combination

    Why:

    CURRENT
    A meta-harness for all your AI agents. Omnigent provides a common layer over Claude Code, Codex, Pi, and the agents you write yourself: swap or combine harnesses without rewriting, keep them in check with policies and sandboxing, and collaborate in real time on the same live session, from any device.
    COPY-PASTE FIX
    Omnigent is a collaborative, multi-device meta-harness for orchestrating and supervising all your AI agents. It provides a common layer over Claude Code, Codex, Pi, and custom agents, enabling real-time collaboration, sandboxing, and seamless multi-device access for agent development and supervision.
  • mediumtopics#2
    Expand GitHub Topics with more specific keywords

    Why:

    CURRENT
    agents, ai, ai-agents, developer-tools, llm, ml, python
    COPY-PASTE FIX
    agents, ai, ai-agents, developer-tools, llm, ml, python, agent-orchestration, multi-agent-systems, collaborative-ai, ai-development-environment, ai-sandbox, agent-harness
  • lowreadme#3
    Add an introductory sentence to the 'Why Omnigent?' section

    Why:

    COPY-PASTE FIX
    Add this sentence before the bullet points in the 'Why Omnigent?' section: 'Omnigent uniquely combines powerful agent orchestration with a real-time, collaborative, and multi-device development environment, offering several key advantages:'

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 omnigent-ai/omnigent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. run-llama/llama_index · recommended 1×
  3. microsoft/semantic-kernel · recommended 1×
  4. deepset-ai/haystack · recommended 1×
  5. joaomdmoura/crewAI · recommended 1×
  • CATEGORY QUERY
    How can I orchestrate and supervise multiple AI agents from different providers in one session?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    4. Haystack (deepset-ai/haystack)
    5. CrewAI (joaomdmoura/crewAI)
    6. FastAPI (tiangolo/fastapi)
    7. Flask (pallets/flask)
    8. Django (django/django)
    9. Zapier NLA
    10. Make

    AI recommended 10 alternatives but never named omnigent-ai/omnigent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools allow real-time collaboration and multi-device access for developing AI agents?
    you: not recommended
    AI recommended (in order):
    1. Google Colaboratory
    2. JupyterLab
    3. Visual Studio Code
    4. Deepnote
    5. Databricks Workspace
    6. GitHub Codespaces

    AI recommended 6 alternatives but never named omnigent-ai/omnigent. 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 omnigent-ai/omnigent?
    pass
    AI named omnigent-ai/omnigent explicitly

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

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

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

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