RRepoGEO

REPOGEO REPORT · LITE

Yvictor/TradingGym

Default branch master · commit 08bb534f · scanned 5/13/2026, 5:03:11 AM

GitHub: 1,872 stars · 369 forks

AI VISIBILITY SCORE
28 /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
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 Yvictor/TradingGym, 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 statement to highlight OpenAI Gym compatibility for financial trading

    Why:

    CURRENT
    TradingGym is a toolkit for training and backtesting the reinforcement learning algorithms. This was inspired by OpenAI Gym and imitated the framework form.
    COPY-PASTE FIX
    TradingGym is an **OpenAI Gym-compatible environment** specifically designed for **training and backtesting reinforcement learning algorithms in financial trading**. It provides a robust toolkit for simulating trading strategies and evaluating AI agents.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/Yvictor/TradingGym
  • mediumtopics#3
    Add 'openai-gym' to the repository topics

    Why:

    CURRENT
    backtest, backtesting-trading-strategies, python, reinforcement-learning, trading, trading-api, trading-bot, trading-platform, trading-simulator, trading-strategies
    COPY-PASTE FIX
    backtest, backtesting-trading-strategies, python, reinforcement-learning, trading, trading-api, trading-bot, trading-platform, trading-simulator, trading-strategies, openai-gym

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 Yvictor/TradingGym
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
mementum/backtrader
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. mementum/backtrader · recommended 2×
  2. QuantConnect/Lean · recommended 2×
  3. quantopian/zipline · recommended 2×
  4. openai/gym · recommended 1×
  5. Farama-Foundation/Gymnasium · recommended 1×
  • CATEGORY QUERY
    How to simulate and backtest reinforcement learning trading strategies in Python?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym (openai/gym)
    2. Gymnasium (Farama-Foundation/Gymnasium)
    3. Stable Baselines3 (DLR-RM/stable-baselines3)
    4. Backtrader (mementum/backtrader)
    5. Lean Engine (QuantConnect/Lean)
    6. Zipline (quantopian/zipline)
    7. FinRL (AI4Finance-LLC/FinRL)
    8. Pandas (pandas-dev/pandas)
    9. yfinance (ranaroussi/yfinance)
    10. pandas_datareader (pydata/pandas-datareader)

    AI recommended 10 alternatives but never named Yvictor/TradingGym. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python environment to train and evaluate algorithmic trading agents.
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean Engine) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Backtrader (mementum/backtrader)
    4. PyAlgoTrade (gbeced/pyalgotrade)
    5. Catalyst (enigmampc/catalyst)
    6. OpenBB Terminal (OpenBB-finance/OpenBBTerminal)

    AI recommended 6 alternatives but never named Yvictor/TradingGym. 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 Yvictor/TradingGym?
    pass
    AI did not name Yvictor/TradingGym — 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 Yvictor/TradingGym in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Yvictor/TradingGym 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 Yvictor/TradingGym solve, and who is the primary audience?
    pass
    AI named Yvictor/TradingGym explicitly

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

Embed your GEO score

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