RRepoGEO

REPOGEO REPORT · LITE

charliedream1/ai_quant_trade

Default branch master · commit fd4d491c · scanned 6/25/2026, 12:36:55 AM

GitHub: 5,835 stars · 1,117 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 charliedream1/ai_quant_trade, 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
    Add an English translation to the repository description

    Why:

    CURRENT
    股票AI操盘手：从学习、模拟到实盘，一站式平台。包含股票知识、策略实例、大模型、因子挖掘、传统策略、机器学习、深度学习、强化学习、图网络、高频交易、C++部署和聚宽实例代码等，可以方便学习、模拟及实盘交易
    COPY-PASTE FIX
    An all-in-one AI quantitative trading platform for learning, simulation, and live trading. It covers stock market knowledge, strategy examples, large language models (LLMs), factor mining, traditional strategies, machine learning, deep learning, reinforcement learning, graph neural networks, high-frequency trading, C++ deployment, and Juyuan (JoinQuant) example code, facilitating easy learning, simulation, and live trading.
  • highhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Add a URL to your project's official homepage or documentation site in the repository settings.
  • mediumreadme#3
    Add a prominent English title and subtitle to the README

    Why:

    CURRENT
    # 🤖 AI量化交易操盘手

**一站式AI量化交易平台 · 从学习、模拟到实盘ENGLISH VERSION**
    COPY-PASTE FIX
    # 🤖 AI Quantitative Trading Platform
**An All-in-One Platform for Learning, Simulation, and Live Trading with AI**

# 🤖 AI量化交易操盘手
**一站式AI量化交易平台 · 从学习、模拟到实盘ENGLISH VERSION**

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 charliedream1/ai_quant_trade
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
QuantConnect/Lean
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. QuantConnect/Lean · recommended 2×
  2. quantopian/zipline · recommended 2×
  3. mementum/backtrader · recommended 2×
  4. enigmampc/catalyst · recommended 1×
  5. fynance/fynance · recommended 1×
  • CATEGORY QUERY
    What are the best open-source AI platforms for learning and deploying trading strategies?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Backtrader (mementum/backtrader)
    4. Catalyst (by Enigma) (enigmampc/catalyst)
    5. Fynance (fynance/fynance)
    6. OpenBB Terminal (OpenBB-finance/OpenBBTerminal)

    AI recommended 6 alternatives but never named charliedream1/ai_quant_trade. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I implement deep learning and reinforcement learning for high-frequency trading?
    you: not recommended
    AI recommended (in order):
    1. NumPy (numpy/numpy)
    2. SciPy (scipy/scipy)
    3. Pandas (pandas-dev/pandas)
    4. Scikit-learn (scikit-learn/scikit-learn)
    5. TensorFlow (tensorflow/tensorflow)
    6. Keras (keras-team/keras)
    7. PyTorch (pytorch/pytorch)
    8. Ray RLlib (ray-project/ray)
    9. Stable Baselines3 (DLR-RM/stable-baselines3)
    10. OpenAI Gym (openai/gym)
    11. Farama Gymnasium (Farama-Foundation/Gymnasium)
    12. Zipline (quantopian/zipline)
    13. QuantConnect (QuantConnect/Lean)
    14. Backtrader (mementum/backtrader)

    AI recommended 14 alternatives but never named charliedream1/ai_quant_trade. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    warn

    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 charliedream1/ai_quant_trade?
    pass
    AI did not name charliedream1/ai_quant_trade — 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 charliedream1/ai_quant_trade in production, what risks or prerequisites should they evaluate first?
    pass
    AI named charliedream1/ai_quant_trade 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 charliedream1/ai_quant_trade solve, and who is the primary audience?
    pass
    AI did not name charliedream1/ai_quant_trade — 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?

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charliedream1/ai_quant_trade — 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