RRepoGEO

REPOGEO REPORT · LITE

star23/Day1Global-Skills

Default branch main · commit 562c14b0 · scanned 6/4/2026, 2:12:56 AM

GitHub: 901 stars · 147 forks

AI VISIBILITY SCORE
22 /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
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 star23/Day1Global-Skills, 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
  • highabout#1
    Update the 'About' description to clarify purpose for AI agents

    Why:

    CURRENT
    Day1Global Skills Share: US Stock, Macro Market, Crypto
    COPY-PASTE FIX
    Investment analysis skills for AI agents, covering tech earnings, macro markets, and crypto cycles.
  • hightopics#2
    Add specific topics for AI agent investment analysis

    Why:

    COPY-PASTE FIX
    ai-agents, investment-analysis, quantitative-finance, stock-market, crypto, bitcoin, macroeconomics, financial-modeling, value-investing, market-sentiment
  • mediumreadme#3
    Strengthen the README's opening to emphasize AI agent focus

    Why:

    CURRENT
    # Day1Global-Skills

[English](#english) | [中文](#中文)

<a id="english"></a>

## English

Investment Analysis Skills for AI Agents — covering tech earnings, value investing, market sentiment, macro liquidity, and Bitcoin cycle analysis.
    COPY-PASTE FIX
    # Day1Global-Skills: Institutional-Grade Investment Analysis Skills for AI Agents

[English](#english) | [中文](#中文)

<a id="english"></a>

## English

This repository provides a suite of institutional-grade investment analysis skills specifically designed for AI agents, covering tech earnings, value investing, market sentiment, macro liquidity, and Bitcoin cycle analysis.

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 star23/Day1Global-Skills
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. quantopian/pyfolio · recommended 1×
  3. quantopian/zipline · recommended 1×
  4. mementum/backtrader · recommended 1×
  5. alpacahq/alpaca-py · recommended 1×
  • CATEGORY QUERY
    What are the best libraries for AI agents to perform detailed investment analysis?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean) (QuantConnect/Lean)
    2. Pyfolio (quantopian/pyfolio)
    3. Zipline (quantopian/zipline)
    4. Backtrader (mementum/backtrader)
    5. Alpaca-py (alpacahq/alpaca-py)
    6. TA-Lib (Technical Analysis Library) (TA-Lib/ta-lib)
    7. Arch (bashtage/arch)

    AI recommended 7 alternatives but never named star23/Day1Global-Skills. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How can I analyze tech stock earnings and Bitcoin market cycles for investment decisions?
    you: not recommended
    AI recommended (in order):
    1. Bloomberg Terminal
    2. Refinitiv Eikon
    3. FactSet
    4. TradingView
    5. CoinMetrics
    6. Glassnode
    7. YCharts

    AI recommended 7 alternatives but never named star23/Day1Global-Skills. 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 star23/Day1Global-Skills?
    pass
    AI did not name star23/Day1Global-Skills — 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 star23/Day1Global-Skills in production, what risks or prerequisites should they evaluate first?
    pass
    AI named star23/Day1Global-Skills 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 star23/Day1Global-Skills solve, and who is the primary audience?
    pass
    AI did not name star23/Day1Global-Skills — 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?

Embed your GEO score

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star23/Day1Global-Skills — 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