RRepoGEO

REPOGEO REPORT · LITE

TradeMaster-NTU/TradeMaster

Default branch 1.0.0 · commit 1747cc18 · scanned 6/21/2026, 7:12:12 AM

GitHub: 2,787 stars · 526 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)

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

AI VISIBILITY SCORE
35 /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
3 / 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 TradeMaster-NTU/TradeMaster, 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
  • highhomepage#1
    Add homepage URL to repository settings

    Why:

    COPY-PASTE FIX
    https://trademaster.readthedocs.io/en/latest/
  • highreadme#2
    Strengthen README's opening paragraph to emphasize full platform capabilities

    Why:

    CURRENT
    TradeMaster is a first-of-its kind, best-in-class __open-source platform__ for __quantitative trading (QT)__ empowered by __reinforcement learning (RL)__, which covers the __full pipeline__ for the design, implementation, evaluation and deployment of RL-based algorithms.
    COPY-PASTE FIX
    TradeMaster is a first-of-its kind, best-in-class __open-source platform__ for __quantitative trading (QT)__ empowered by __reinforcement learning (RL)__, which covers the __full pipeline__ for the design, implementation, evaluation and deployment of RL-based algorithms. It provides researchers and practitioners with a comprehensive toolkit to build, backtest, and deploy sophisticated RL-based investment strategies, bridging the gap between academic research and practical application.
  • mediumtopics#3
    Add more specific topics to enhance category visibility

    Why:

    CURRENT
    finance, fintech, investment-strategies, jupyter-notebook, machine-learning, python, pytorch, quantitative-trading, reinforcement-learning, stock-market, trading-platform
    COPY-PASTE FIX
    finance, fintech, investment-strategies, jupyter-notebook, machine-learning, python, pytorch, quantitative-trading, reinforcement-learning, stock-market, trading-platform, backtesting, algorithmic-trading, strategy-development

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 TradeMaster-NTU/TradeMaster
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Baselines3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Baselines3 · recommended 1×
  2. Gymnasium · recommended 1×
  3. Pandas · recommended 1×
  4. PyTorch · recommended 1×
  5. Backtrader · recommended 1×
  • CATEGORY QUERY
    How to build quantitative trading strategies using reinforcement learning in Python?
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3
    2. Gymnasium
    3. Pandas
    4. PyTorch
    5. Backtrader
    6. TA-Lib
    7. Optuna

    AI recommended 7 alternatives but never named TradeMaster-NTU/TradeMaster. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source platform for developing and evaluating RL-based investment strategies.
    you: not recommended
    AI recommended (in order):
    1. FinRL (AI4Finance-LLC/FinRL)
    2. OpenAI Gym (openai/gym)
    3. Stable Baselines3 (DLR-RM/stable-baselines3)
    4. Ray RLlib (ray-project/ray)
    5. Lean Engine (QuantConnect/Lean)
    6. TF-Agents (tensorflow/agents)
    7. Catalyst (quantopian/catalyst)

    AI recommended 7 alternatives but never named TradeMaster-NTU/TradeMaster. 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 TradeMaster-NTU/TradeMaster?
    pass
    AI named TradeMaster-NTU/TradeMaster explicitly

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

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

    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 TradeMaster-NTU/TradeMaster. 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/TradeMaster-NTU/TradeMaster.svg)](https://repogeo.com/en/r/TradeMaster-NTU/TradeMaster)
HTML
<a href="https://repogeo.com/en/r/TradeMaster-NTU/TradeMaster"><img src="https://repogeo.com/badge/TradeMaster-NTU/TradeMaster.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

TradeMaster-NTU/TradeMaster — 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