RRepoGEO

REPOGEO REPORT · LITE

Y-Research-SBU/QuantAgent

Default branch main · commit 92519f80 · scanned 5/8/2026, 2:47:47 PM

GitHub: 2,450 stars · 546 forks

AI VISIBILITY SCORE
33 /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
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 Y-Research-SBU/QuantAgent, 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 core value proposition immediately after the title

    Why:

    CURRENT
    The README starts with author lists and links after the H2.
    COPY-PASTE FIX
    Add a concise, problem-solution oriented paragraph right after the H2, e.g., "QuantAgent is a research framework that applies price-driven multi-agent Large Language Models (LLMs) to high-frequency trading. It provides tools and methodologies for researchers and practitioners to design, simulate, and evaluate sophisticated AI trading strategies that leverage LLM capabilities for market analysis and decision-making."
  • hightopics#2
    Expand repository topics to include specific financial and trading terms

    Why:

    CURRENT
    agentic-ai, large-language-models
    COPY-PASTE FIX
    agentic-ai, large-language-models, quantitative-trading, high-frequency-trading, financial-llms, multi-agent-systems, algorithmic-trading, market-simulation, financial-ai
  • mediumabout#3
    Refine the repository description for clarity and specificity

    Why:

    CURRENT
    Official Repository for QuantAgent
    COPY-PASTE FIX
    QuantAgent: A research framework for price-driven multi-agent LLMs in high-frequency trading and financial market simulation.

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 Y-Research-SBU/QuantAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Quandl (now Nasdaq Data Link)
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Quandl (now Nasdaq Data Link) · recommended 1×
  2. Alpaca Markets · recommended 1×
  3. ranaroussi/yfinance · recommended 1×
  4. NewsAPI.org · recommended 1×
  5. GDELT Project · recommended 1×
  • CATEGORY QUERY
    How can I use AI agents and large language models for automated trading strategies?
    you: not recommended
    AI recommended (in order):
    1. Quandl (now Nasdaq Data Link)
    2. Alpaca Markets
    3. yfinance (ranaroussi/yfinance)
    4. NewsAPI.org
    5. GDELT Project
    6. Pandas (pandas-dev/pandas)
    7. NumPy (numpy/numpy)
    8. Scikit-learn (scikit-learn/scikit-learn)
    9. TensorFlow (tensorflow/tensorflow)
    10. PyTorch (pytorch/pytorch)
    11. Hugging Face Transformers (huggingface/transformers)
    12. BERT
    13. RoBERTa
    14. DistilBERT
    15. OpenAI API
    16. LangChain (langchain-ai/langchain)
    17. LlamaIndex (run-llama/llama_index)
    18. Zipline (quantopian/zipline)
    19. Backtrader (mementum/backtrader)
    20. QuantConnect (Lean Engine) (QuantConnect/Lean)
    21. PyAlgoTrade (gbeced/pyalgotrade)
    22. Interactive Brokers API (IBKR API)
    23. MetaTrader 5 (MT5) (MetaQuotes/MetaTrader5)
    24. Prometheus (prometheus/prometheus)
    25. Grafana (grafana/grafana)
    26. Slack APIs
    27. Telegram APIs
    28. FinBERT

    AI recommended 28 alternatives but never named Y-Research-SBU/QuantAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for tools to develop LLM-powered multi-agent systems for financial market analysis.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. AutoGen
    3. CrewAI
    4. LlamaIndex
    5. Haystack
    6. OpenAI Assistants API
    7. transformers
    8. requests
    9. pandas

    AI recommended 9 alternatives but never named Y-Research-SBU/QuantAgent. 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 Y-Research-SBU/QuantAgent?
    pass
    AI named Y-Research-SBU/QuantAgent explicitly

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

  • If a team adopts Y-Research-SBU/QuantAgent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Y-Research-SBU/QuantAgent 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 Y-Research-SBU/QuantAgent solve, and who is the primary audience?
    pass
    AI did not name Y-Research-SBU/QuantAgent — 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?

Embed your GEO score

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

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/Y-Research-SBU/QuantAgent.svg)](https://repogeo.com/en/r/Y-Research-SBU/QuantAgent)
HTML
<a href="https://repogeo.com/en/r/Y-Research-SBU/QuantAgent"><img src="https://repogeo.com/badge/Y-Research-SBU/QuantAgent.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

Y-Research-SBU/QuantAgent — 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