RRepoGEO

REPOGEO REPORT · LITE

0xemmkty/QuantMuse

Default branch main · commit f86ede35 · scanned 5/18/2026, 8:33:25 PM

GitHub: 2,530 stars · 534 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 0xemmkty/QuantMuse, 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 README's opening to emphasize 'full-stack system' and C++ core

    Why:

    CURRENT
    # 🚀 Quantitative Trading System

> **A comprehensive quantitative trading system with AI-powered analysis, real-time data processing, and advanced risk management**
    COPY-PASTE FIX
    # 🚀 QuantMuse: A Production-Ready Full-Stack Quantitative Trading System with C++ Core

> **QuantMuse is a comprehensive, production-ready quantitative trading *platform* featuring a high-performance C++ core engine, AI-powered analysis, real-time data processing, and advanced risk management for serious quants and developers.**
  • mediumhomepage#2
    Add a homepage URL to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    Add the official project website URL to the repository's 'About' section.
  • lowtopics#3
    Expand repository topics to include key technologies and specific domains

    Why:

    CURRENT
    machine-learning, python, quantitative-trading
    COPY-PASTE FIX
    machine-learning, python, quantitative-trading, algorithmic-trading, cpp, financial-engineering, real-time-data, trading-platform

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 0xemmkty/QuantMuse
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Zipline
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Zipline · recommended 1×
  2. Lean Engine · recommended 1×
  3. Backtrader · recommended 1×
  4. PyAlgoTrade · recommended 1×
  5. TA-Lib · recommended 1×
  • CATEGORY QUERY
    Looking for a Python library for AI-driven quantitative trading strategies and market analysis.
    you: not recommended
    AI recommended (in order):
    1. Zipline
    2. Lean Engine
    3. Backtrader
    4. PyAlgoTrade
    5. TA-Lib
    6. Scikit-learn
    7. TensorFlow
    8. PyTorch

    AI recommended 8 alternatives but never named 0xemmkty/QuantMuse. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need a comprehensive system for real-time financial data processing and algorithmic trading with risk management.
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean Engine) (QuantConnect/Lean)
    2. DolphinDB (dolphindb/DolphinDB)
    3. LMAX Exchange
    4. Pandas (pandas-dev/pandas)
    5. NumPy (numpy/numpy)
    6. scikit-learn (scikit-learn/scikit-learn)
    7. asyncio
    8. OpenGamma Platform (OpenGamma/OG-Platform)
    9. AlgoTrader
    10. IBKR API (Interactive Brokers API)
    11. QuantHouse

    AI recommended 11 alternatives but never named 0xemmkty/QuantMuse. 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 0xemmkty/QuantMuse?
    pass
    AI named 0xemmkty/QuantMuse explicitly

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

  • If a team adopts 0xemmkty/QuantMuse in production, what risks or prerequisites should they evaluate first?
    pass
    AI named 0xemmkty/QuantMuse 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 0xemmkty/QuantMuse solve, and who is the primary audience?
    pass
    AI named 0xemmkty/QuantMuse 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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0xemmkty/QuantMuse — 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