RRepoGEO

REPOGEO REPORT · LITE

0xemmkty/QuantMuse

Default branch main · commit f86ede35 · scanned 6/30/2026, 3:12:48 AM

GitHub: 2,704 stars · 560 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 the README's main heading and opening paragraph

    Why:

    CURRENT
    # 🚀 Quantitative Trading System

> **A comprehensive quantitative trading system with AI-powered analysis, real-time data processing, and advanced risk management**

## 📋 Table of Contents

- [Overview](#overview)
- [Features](#features)
- [Architecture](#architecture)
- [Quick Start](#quick-start)
- [Installation](#installation)
- [Usage Examples](#usage-examples)
- [Documentation](#documentation)
- [Contributing](#contributing)
- [License](#license)

## 🎯 Overview

This is a production-ready quantitative trading system that combines traditional financial analysis with cutting-edge AI/ML technologies.
    COPY-PASTE FIX
    # 🚀 QuantMuse: Production-Ready AI-Powered Quantitative Trading System

> **QuantMuse is a comprehensive, production-ready quantitative trading system with AI-powered analysis, real-time data processing, and advanced risk management, designed for quantitative analysts and algorithmic traders.**

## 📋 Table of Contents

- [Overview](#overview)
- [Features](#features)
- [Architecture](#architecture)
- [Quick Start](#quick-start)
- [Installation](#installation)
- [Usage Examples](#usage-examples)
- [Documentation](#documentation)
- [Contributing](#contributing)
- [License](#license)

## 🎯 Overview

This system combines traditional financial analysis with cutting-edge AI/ML technologies.
  • mediumtopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    machine-learning, python, quantitative-trading
    COPY-PASTE FIX
    machine-learning, python, quantitative-trading, algorithmic-trading, ai-trading, real-time-data, financial-analysis, llm-integration
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/0xemmkty/QuantMuse

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. Backtrader · recommended 1×
  3. QuantConnect (Lean Engine) · recommended 1×
  4. PyAlgoTrade · recommended 1×
  5. TA-Lib · recommended 1×
  • CATEGORY QUERY
    What are some Python libraries for building AI-driven quantitative trading systems?
    you: not recommended
    AI recommended (in order):
    1. Zipline
    2. Backtrader
    3. QuantConnect (Lean Engine)
    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
    Seeking a comprehensive trading platform with real-time data processing and advanced risk management features.
    you: not recommended
    AI recommended (in order):
    1. FlexTrade (FlexTRADER EMS/OMS)
    2. Charles River Development (Charles River IMS)
    3. Bloomberg Terminal
    4. Refinitiv Eikon (with Eikon Messenger and FXall for FX)
    5. Fidessa (now part of ION Group)
    6. Trading Technologies (TT Platform)

    AI recommended 6 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?

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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