RRepoGEO

REPOGEO REPORT · LITE

ByteDance-Seed/m3-agent

Default branch master · commit 0e3e4193 · scanned 5/10/2026, 3:07:48 PM

GitHub: 1,332 stars · 111 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 ByteDance-Seed/m3-agent, 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 to clearly state its purpose

    Why:

    CURRENT
    <h1 style="text-align: center;">Seeing, Listening, Remembering, and Reasoning: A Multimodal Agent with Long-Term Memory<br>ICLR 2026</h1>
    COPY-PASTE FIX
    # M3-Agent: A Multimodal AI Agent Framework with Long-Term Memory

M3-Agent enables AI agents to process real-time visual and auditory inputs, build semantic and episodic memory, and perform autonomous multi-turn reasoning.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    multimodal-ai, ai-agent, long-term-memory, reasoning, multimodal-llm, robotics, computer-vision, audio-processing
  • mediumabout#3
    Add a concise description to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    M3-Agent is a multimodal AI agent framework equipped with long-term memory, capable of processing real-time visual and auditory inputs for autonomous reasoning and task accomplishment.

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 ByteDance-Seed/m3-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenAI GPT-4o
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenAI GPT-4o · recommended 1×
  2. GPT-4 with Vision · recommended 1×
  3. OpenAI Whisper · recommended 1×
  4. facebookresearch/faiss · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    How to build an AI agent that processes real-time visual and auditory inputs with long-term memory?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4o
    2. GPT-4 with Vision
    3. OpenAI Whisper
    4. FAISS (facebookresearch/faiss)
    5. Pinecone
    6. Weaviate (weaviate/weaviate)
    7. LangChain (langchain-ai/langchain)
    8. LlamaIndex (run-llama/llama_index)
    9. Hugging Face Transformers (huggingface/transformers)
    10. ChromaDB (chromadb/chroma)
    11. Qdrant (qdrant/qdrant)
    12. Google Cloud Vertex AI
    13. Gemini Pro Vision
    14. Gemini 1.5 Pro
    15. Google's Speech-to-Text API
    16. AlloyDB for PostgreSQL
    17. Cloud Spanner
    18. Firestore
    19. Microsoft Azure AI Services
    20. Azure OpenAI Service
    21. Azure AI Vision
    22. Azure AI Speech
    23. Azure Cosmos DB
    24. Azure SQL Database
    25. Rasa (RasaHQ/rasa)
    26. SpaCy (explosion/spaCy)
    27. NLTK (nltk/nltk)
    28. TensorFlow (tensorflow/tensorflow)
    29. PyTorch (pytorch/pytorch)
    30. Mozilla DeepSpeech (mozilla/DeepSpeech)
    31. PostgreSQL
    32. Redis (redis/redis)

    AI recommended 32 alternatives but never named ByteDance-Seed/m3-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an agent framework enabling autonomous multi-turn reasoning and memory-based task accomplishment.
    you: not recommended
    AI recommended (in order):
    1. AutoGPT
    2. LangChain
    3. LlamaIndex
    4. BabyAGI
    5. Microsoft AutoGen
    6. Haystack
    7. CrewAI

    AI recommended 7 alternatives but never named ByteDance-Seed/m3-agent. 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 ByteDance-Seed/m3-agent?
    pass
    AI did not name ByteDance-Seed/m3-agent — 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 ByteDance-Seed/m3-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named ByteDance-Seed/m3-agent 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 ByteDance-Seed/m3-agent solve, and who is the primary audience?
    pass
    AI named ByteDance-Seed/m3-agent explicitly

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

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ByteDance-Seed/m3-agent — 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