RRepoGEO

REPOGEO REPORT · LITE

OpenMOSS/AnyGPT

Default branch main · commit 282b58fa · scanned 6/14/2026, 5:58:06 AM

GitHub: 882 stars · 76 forks

AI VISIBILITY SCORE
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
2 / 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 OpenMOSS/AnyGPT, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README H1 to be more project-centric

    Why:

    CURRENT
    # Official Repository for paper "AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling"
    COPY-PASTE FIX
    # AnyGPT: A Unified Multimodal LLM for Any-to-Any Modality Processing with Discrete Sequence Modeling
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT License) in the root of the repository.

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 OpenMOSS/AnyGPT
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 2×
  2. PyTorch · recommended 1×
  3. torchvision · recommended 1×
  4. torchaudio · recommended 1×
  5. TensorFlow · recommended 1×
  • CATEGORY QUERY
    How can I build an AI that understands and generates multiple media types?
    you: not recommended
    AI recommended (in order):
    1. PyTorch
    2. torchvision
    3. Hugging Face Transformers
    4. torchaudio
    5. TensorFlow
    6. Keras
    7. tf.keras.applications
    8. tf.image
    9. tf.text
    10. tf.audio
    11. TensorFlow Lite for Microcontrollers
    12. OpenAI API
    13. GPT-4V
    14. DALL-E 3
    15. Whisper
    16. GPT-4
    17. GPT-3.5
    18. JAX
    19. Flax
    20. Haiku
    21. DeepMind's Perceiver IO

    AI recommended 21 alternatives but never named OpenMOSS/AnyGPT. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What LLM frameworks handle speech, text, images, and music with unified discrete tokens?
    you: not recommended
    AI recommended (in order):
    1. Google's Pathways / PaLM-E / Gemini
    2. OpenAI's GPT-4
    3. Meta's ImageBind
    4. Microsoft's Kosmos-1 / Kosmos-2
    5. Hugging Face Transformers

    AI recommended 5 alternatives but never named OpenMOSS/AnyGPT. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 OpenMOSS/AnyGPT?
    pass
    AI did not name OpenMOSS/AnyGPT — likely talking about a different project

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

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

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

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OpenMOSS/AnyGPT — 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