RRepoGEO

REPOGEO REPORT · LITE

alpha-xone/xbbg

Default branch main · commit d910396b · scanned 6/17/2026, 11:36:37 AM

GitHub: 800 stars · 65 forks

AI VISIBILITY SCORE
40 /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
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 alpha-xone/xbbg, 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
    Add a concise, direct value proposition at the very top of the README

    Why:

    COPY-PASTE FIX
    xbbg is a high-performance Python and Node.js library for intuitive, Pandas/Polars-centric access to Bloomberg Terminal data and functionality, powered by Rust.
  • hightopics#2
    Add more specific topics related to Bloomberg Terminal integration

    Why:

    CURRENT
    apache-arrow, blpapi, finance, financial-data, fintech, market-data, napi-rs, nodejs, pandas, polars, pyo3, python, quantitative-finance, rust, streaming, timeseries
    COPY-PASTE FIX
    apache-arrow, blpapi, bloomberg, bloomberg-terminal, finance, financial-data, fintech, market-data, napi-rs, nodejs, pandas, polars, pyo3, python, quantitative-finance, rust, streaming, timeseries
  • mediumreadme#3
    Strengthen the 'What is xbbg?' section's opening paragraph

    Why:

    COPY-PASTE FIX
    Ensure the first paragraph of the 'What is xbbg?' section clearly states: 'xbbg is a high-performance, Rust-powered library providing an intuitive, Pandas and Polars-centric interface for programmatic access to Bloomberg Terminal data and functionality. It simplifies complex `blpapi` interactions for financial professionals and quantitative analysts, enabling efficient retrieval of real-time and historical market data.'

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 alpha-xone/xbbg
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
apache/flink
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. apache/flink · recommended 2×
  2. Polygon.io · recommended 1×
  3. Alpaca Markets · recommended 1×
  4. Interactive Brokers (IBKR) API · recommended 1×
  5. EOD Historical Data · recommended 1×
  • CATEGORY QUERY
    How to efficiently retrieve real-time financial market data for quantitative analysis in Python?
    you: not recommended
    AI recommended (in order):
    1. Polygon.io
    2. Alpaca Markets
    3. Interactive Brokers (IBKR) API
    4. EOD Historical Data
    5. Quandl (now Nasdaq Data Link)
    6. yfinance
    7. Tiingo

    AI recommended 7 alternatives but never named alpha-xone/xbbg. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a performant library to integrate streaming financial data with Polars or Pandas dataframes.
    you: not recommended
    AI recommended (in order):
    1. Apache Flink (apache/flink)
    2. PyFlink (apache/flink)
    3. Confluent Kafka
    4. confluent-kafka-python (confluentinc/confluent-kafka-python)
    5. kafka-python (dpkp/kafka-python)
    6. Faust (robinhood/faust)
    7. aiohttp (aio-libs/aiohttp)
    8. websockets (python-websockets/websockets)
    9. pyarrow (apache/arrow)

    AI recommended 9 alternatives but never named alpha-xone/xbbg. 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 alpha-xone/xbbg?
    pass
    AI named alpha-xone/xbbg explicitly

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

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

    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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alpha-xone/xbbg — 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