RRepoGEO

REPOGEO REPORT · LITE

run-bigpig/jcp

Default branch master · commit 44af274e · scanned 6/28/2026, 5:57:27 AM

GitHub: 1,222 stars · 286 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 run-bigpig/jcp, 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 README H1 to explicitly state core function in English

    Why:

    CURRENT
    # 韭菜盘 (JCP AI)
    COPY-PASTE FIX
    # 韭菜盘 (JCP AI) - AI-Powered Stock Analysis System
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai, stock-analysis, multi-agent, wails, go, react, desktop-app, financial-data, investment-tools, a-share
  • mediumhomepage#3
    Add a homepage URL to the repository

    Why:

    COPY-PASTE FIX
    https://github.com/run-bigpig/jcp

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 run-bigpig/jcp
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mirasol
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Mirasol · recommended 1×
  2. AutoGen · recommended 1×
  3. LangChain · recommended 1×
  4. CrewAI · recommended 1×
  5. scikit-learn · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered desktop stock analysis system with multi-agent collaboration?
    you: not recommended
    AI recommended (in order):
    1. Mirasol
    2. AutoGen
    3. LangChain
    4. CrewAI
    5. scikit-learn
    6. PyTorch
    7. TensorFlow/Keras
    8. XGBoost/LightGBM
    9. yfinance
    10. Alpha Vantage API
    11. Quandl (now Nasdaq Data Link)
    12. Pandas
    13. SQLAlchemy
    14. PyQt/PySide
    15. Tkinter
    16. Streamlit
    17. NLTK (Natural Language Toolkit)
    18. spaCy
    19. Hugging Face Transformers

    AI recommended 19 alternatives but never named run-bigpig/jcp. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a cross-platform desktop framework for real-time financial market data and AI insights.
    you: not recommended
    AI recommended (in order):
    1. Electron (electron/electron)
    2. Qt (qt/qt5)
    3. Flutter (flutter/flutter)
    4. Avalonia UI (AvaloniaUI/Avalonia)
    5. Tauri (tauri-apps/tauri)
    6. NW.js (nwjs/nw.js)

    AI recommended 6 alternatives but never named run-bigpig/jcp. 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 run-bigpig/jcp?
    pass
    AI named run-bigpig/jcp explicitly

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

  • If a team adopts run-bigpig/jcp in production, what risks or prerequisites should they evaluate first?
    pass
    AI named run-bigpig/jcp 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 run-bigpig/jcp solve, and who is the primary audience?
    pass
    AI named run-bigpig/jcp explicitly

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

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run-bigpig/jcp — 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