RRepoGEO

REPOGEO REPORT · LITE

gityuanbao/share

Default branch master · commit 2a867997 · scanned 5/17/2026, 12:32:36 PM

GitHub: 1,151 stars · 85 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
30 /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
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 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
  • highabout#1
    Add a concise description and clarify README's primary focus

    Why:

    COPY-PASTE FIX
    For the repository description: "A multi-purpose repository featuring a Python project for collecting diverse financial market data (stocks, futures, macro, news) using AKShare, alongside various AI-related tutorials and resources."
    
    For the README, add this sentence directly after the '🌟Welcome to Yuanbao's open-source repository.🌟' line:
    "This repository primarily hosts a Python project for collecting diverse financial market data using AKShare, alongside various AI-related tutorials and resources."
  • hightopics#2
    Add relevant topics to improve categorization

    Why:

    COPY-PASTE FIX
    financial-data, quant-trading, akshare, python, data-collection, ai-tutorials, machine-learning, deep-learning
  • highlicense#3
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the following content (MIT License example; choose the license most appropriate for your project):
    
    ```
    MIT License
    
    Copyright (c) [YEAR] [COPYRIGHT HOLDER]
    
    Permission is hereby granted, free of charge, to any person obtaining a copy
    of this software and associated documentation files (the "Software"), to deal
    in the Software without restriction, including without limitation the rights
    to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
    copies of the Software, and to permit persons to whom the Software is
    furnished to do so, subject to the following conditions:
    
    The above copyright notice and this permission notice shall be included in all
    copies or substantial portions of the Software.
    
    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
    IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
    FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
    AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
    LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
    OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
    SOFTWARE.
    ```

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
yfinance
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. yfinance · recommended 1×
  2. pandas-datareader · recommended 1×
  3. Quandl (now Nasdaq Data Link) · recommended 1×
  4. Alpha Vantage API · recommended 1×
  5. alpha_vantage · recommended 1×
  • CATEGORY QUERY
    What open-source Python tools exist for collecting diverse financial market data?
    you: not recommended
    AI recommended (in order):
    1. yfinance
    2. pandas-datareader
    3. Quandl (now Nasdaq Data Link)
    4. Alpha Vantage API
    5. alpha_vantage
    6. InvestPy
    7. EOD Historical Data

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

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust library to gather stock, futures, and macroeconomic financial data.
    you: not recommended
    AI recommended (in order):
    1. Quandl (now Nasdaq Data Link) (nasdaq-data-link/nasdaq-data-link-python)
    2. yfinance (ranaroussi/yfinance)
    3. Alpha Vantage
    4. Eikon Data API (formerly Refinitiv Eikon) (Refinitiv-API-Samples/eikon-data-api)
    5. Bloomberg Terminal (with Python API) (bloomberg/blpapi-py)
    6. FRED (Federal Reserve Economic Data) API (mortada/fredapi)
    7. Tiingo (tiingo/tiingo-python)

    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 named gityuanbao/share explicitly

    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 named gityuanbao/share explicitly

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

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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