RRepoGEO

REPOGEO REPORT · LITE

gityuanbao/share

Default branch master · commit 2a867997 · scanned 6/28/2026, 3:02:56 PM

GitHub: 1,180 stars · 86 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
17 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 gityuanbao/share, 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
    Clarify the repository's primary purpose in the README and add a concise description

    Why:

    CURRENT
    # 源宝的开源仓库
    COPY-PASTE FIX
    # gityuanbao/share: AI Tutorials & Financial Data Tools

(For GitHub Description field): A collection of open-source projects and tutorials, featuring an AKShare-based financial data collector for A-share, Hong Kong stock, and macroeconomic data, alongside various AI-related guides and resources.
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    python, akshare, financial-data, stock-market, quantitative-finance, ai-tutorials, deep-learning, machine-learning, data-collection, generative-ai
  • highlicense#3
    Add a LICENSE file to clarify usage rights

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT or Apache-2.0) to the repository root to specify the terms of use for all included projects and resources.

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 gityuanbao/share
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ranaroussi/yfinance
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ranaroussi/yfinance · recommended 2×
  2. waditu/tushare · recommended 1×
  3. Wind API · recommended 1×
  4. akfamily/akshare · recommended 1×
  5. Quandl · recommended 1×
  • CATEGORY QUERY
    How can I programmatically gather A-share, Hong Kong stock, and macroeconomic data?
    you: not recommended
    AI recommended (in order):
    1. Tushare (waditu/tushare)
    2. Wind API
    3. AkShare (akfamily/akshare)
    4. yfinance (ranaroussi/yfinance)
    5. Quandl
    6. Refinitiv Eikon/Workspace API
    7. FRED API

    AI recommended 7 alternatives but never named gityuanbao/share. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python library to collect real-time stock market and financial news data.
    you: not recommended
    AI recommended (in order):
    1. Alpaca-py (alpacahq/alpaca-py)
    2. EOD Historical Data (eodhistoricaldata/eod-historical-data-python)
    3. Polygon.io (polygon-io/client-python)
    4. yfinance (ranaroussi/yfinance)
    5. NewsAPI (mattlisiv/newsapi-python)
    6. Beautiful Soup (crummy/beautifulsoup4)
    7. Requests (psf/requests)

    AI recommended 7 alternatives but never named gityuanbao/share. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 gityuanbao/share?
    pass
    AI did not name gityuanbao/share — 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 gityuanbao/share in production, what risks or prerequisites should they evaluate first?
    pass
    AI named gityuanbao/share 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 gityuanbao/share solve, and who is the primary audience?
    pass
    AI did not name gityuanbao/share — 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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MARKDOWN (README)
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gityuanbao/share — 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