RRepoGEO

REPOGEO REPORT · LITE

asavinov/intelligent-trading-bot

Default branch master · commit d8478ba2 · scanned 5/27/2026, 4:08:12 PM

GitHub: 1,702 stars · 383 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 asavinov/intelligent-trading-bot, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Reposition the core value proposition at the top of the README

    Why:

    CURRENT
    The current README starts with ASCII art and a Telegram link before the project description.
    COPY-PASTE FIX
    Move the project's core description, 'The aim of the project is to develop an intelligent trading bot for automated trading including cryptocurrencies using state-of-the-art machine learning (ML) algorithms and feature engineering,' to the very top of the README, above any ASCII art or links.
  • lowcomparison#2
    Add a 'Why This Bot?' or 'Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, perhaps titled 'Why Intelligent Trading Bot?' or 'Key Differentiators,' that explicitly outlines how its use of state-of-the-art machine learning and feature engineering for signal generation sets it apart from rule-based or simpler algorithmic trading bots.

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 asavinov/intelligent-trading-bot
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. QuantConnect (Lean) · recommended 1×
  2. Backtrader · recommended 1×
  3. Freqtrade · recommended 1×
  4. Catalyst (Quantopian's crypto framework) · recommended 1×
  5. Gekko · recommended 1×
  • CATEGORY QUERY
    Need a framework for automated crypto trading using machine learning algorithms.
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean)
    2. Backtrader
    3. Freqtrade
    4. Catalyst (Quantopian's crypto framework)
    5. Gekko

    AI recommended 5 alternatives but never named asavinov/intelligent-trading-bot. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an AI-powered solution for generating trading signals and automating cryptocurrency trades.
    you: not recommended
    AI recommended (in order):
    1. 3Commas
    2. Cryptohopper
    3. Pionex
    4. Hummingbot
    5. TradeSanta
    6. HaasOnline

    AI recommended 6 alternatives but never named asavinov/intelligent-trading-bot. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 asavinov/intelligent-trading-bot?
    pass
    AI did not name asavinov/intelligent-trading-bot — 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 asavinov/intelligent-trading-bot in production, what risks or prerequisites should they evaluate first?
    pass
    AI named asavinov/intelligent-trading-bot 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 asavinov/intelligent-trading-bot solve, and who is the primary audience?
    pass
    AI did not name asavinov/intelligent-trading-bot — 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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asavinov/intelligent-trading-bot — 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