RRepoGEO

REPOGEO REPORT · LITE

mshumer/gpt-investor

Default branch main · commit 316c7095 · scanned 6/19/2026, 10:03:03 PM

GitHub: 2,259 stars · 279 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
23 /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
2 / 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 mshumer/gpt-investor, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    An experimental framework for AI investment analysis agents, featuring Claude-Investor for comprehensive stock insights and recommendations using LLMs.
  • highreadme#2
    Reposition the README's opening to clarify the project's scope

    Why:

    CURRENT
    # gpt-investor

[](https://twitter.com/mattshumer_)
# Claude-Investor | The first release in the gpt-investor repo

Claude-Investor is an experimental investment analysis agent that utilizes the Claude 3 Opus and Haiku models to provide comprehensive insights and recommendations for stocks in a given industry. It retrieves financial data, news articles, and analyst ratings for companies, performs sentiment analysis, and generates comparative analyses to rank the companies based on their investment potential.
    COPY-PASTE FIX
    # gpt-investor: LLM-Powered Investment Analysis Agents

This repository, `gpt-investor`, serves as an experimental framework for developing and deploying AI agents that perform comprehensive investment analysis. It leverages large language models (LLMs) to process financial data, news, and market sentiment to generate actionable insights and recommendations.

## Claude-Investor: The First Agent in the gpt-investor Framework

Claude-Investor is an experimental investment analysis agent that utilizes the Claude 3 Opus and Haiku models to provide comprehensive insights and recommendations for stocks in a given industry. It retrieves financial data, news articles, and analyst ratings for companies, performs sentiment analysis, and generates comparative analyses to rank the companies based on their investment potential.

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 mshumer/gpt-investor
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/zipline · recommended 1×
  3. Alpaca Markets API · recommended 1×
  4. scikit-learn/scikit-learn · recommended 1×
  5. tensorflow/tensorflow · recommended 1×
  • CATEGORY QUERY
    How can I use AI to analyze stock market data and generate investment recommendations?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (Lean) (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Alpaca Markets API
    4. `scikit-learn` (scikit-learn/scikit-learn)
    5. `TensorFlow` (tensorflow/tensorflow)
    6. `PyTorch` (pytorch/pytorch)
    7. Keras (keras-team/keras)
    8. Yahoo Finance APIs
    9. `yfinance` (ranaroussi/yfinance)
    10. Alpha Vantage APIs
    11. AWS SageMaker
    12. Google Cloud AI Platform
    13. Azure Machine Learning
    14. OpenBB Terminal (OpenBB-finance/OpenBBTerminal)
    15. ChatGPT
    16. GPT-4

    AI recommended 16 alternatives but never named mshumer/gpt-investor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help compare company financials and market sentiment for stock investment decisions?
    you: not recommended
    AI recommended (in order):
    1. Bloomberg Terminal
    2. Refinitiv Eikon
    3. FactSet
    4. S&P Capital IQ
    5. Yahoo Finance Premium
    6. Seeking Alpha Premium
    7. Finviz Elite

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

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

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mshumer/gpt-investor — 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