RRepoGEO

REPOGEO REPORT · LITE

FlagOpen/RoboBrain2.5

Default branch main · commit af98c932 · scanned 5/30/2026, 8:43:11 PM

GitHub: 1,066 stars · 107 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 FlagOpen/RoboBrain2.5, 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
    Add a concise positioning statement to the README's opening

    Why:

    COPY-PASTE FIX
    Add this sentence immediately after the H1: "RoboBrain 2.5 is a large-scale, open-source, multi-modal, multi-task, and multi-robot foundation model for embodied AI, designed to bridge large language models with robotic control."
  • mediumabout#2
    Expand the repository description with key functionalities

    Why:

    CURRENT
    RoboBrain 2.5: Advanced version of RoboBrain. Depth in Sight, Time in Mind. 🎉🎉🎉
    COPY-PASTE FIX
    RoboBrain 2.5 is an advanced, open-source foundation model for embodied AI, integrating vision, language, and 3D spatial reasoning to enable intelligent robotic control and temporal planning. 🎉🎉🎉
  • lowtopics#3
    Add more specific topics related to robotic control and spatial reasoning

    Why:

    CURRENT
    embodied-ai, multimodel-large-language-model
    COPY-PASTE FIX
    embodied-ai, multimodel-large-language-model, robotic-control, temporal-planning, 3d-spatial-reasoning, foundation-model

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 FlagOpen/RoboBrain2.5
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Habitat-Matterport 3D Research Dataset (HM3D)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Habitat-Matterport 3D Research Dataset (HM3D) · recommended 1×
  2. Habitat-Sim · recommended 1×
  3. AI2-THOR · recommended 1×
  4. RoboTHOR · recommended 1×
  5. ALFRED · recommended 1×
  • CATEGORY QUERY
    Looking for an embodied AI framework that integrates vision, language, and 3D spatial reasoning.
    you: not recommended
    AI recommended (in order):
    1. Habitat-Matterport 3D Research Dataset (HM3D)
    2. Habitat-Sim
    3. AI2-THOR
    4. RoboTHOR
    5. ALFRED
    6. RLBench
    7. OmniGibson
    8. PyBullet

    AI recommended 8 alternatives but never named FlagOpen/RoboBrain2.5. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best multimodal large language models for robotic control and temporal planning?
    you: not recommended
    AI recommended (in order):
    1. GPT-4V
    2. PaLM-E
    3. Gato
    4. ImageBind
    5. RT-X
    6. Llama 2
    7. Mistral
    8. Falcon
    9. CLIP
    10. ViT
    11. OpenFlamingo
    12. LLaVA

    AI recommended 12 alternatives but never named FlagOpen/RoboBrain2.5. 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 FlagOpen/RoboBrain2.5?
    pass
    AI named FlagOpen/RoboBrain2.5 explicitly

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

  • If a team adopts FlagOpen/RoboBrain2.5 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named FlagOpen/RoboBrain2.5 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 FlagOpen/RoboBrain2.5 solve, and who is the primary audience?
    pass
    AI named FlagOpen/RoboBrain2.5 explicitly

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

Embed your GEO score

Drop this badge into the README of FlagOpen/RoboBrain2.5. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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  • Brand-free category queries5 vs 2 in Lite
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