RRepoGEO

REPOGEO REPORT · LITE

ICT-FinD-Lab/alphagen

Default branch master · commit 259687e8 · scanned 6/28/2026, 8:58:07 AM

GitHub: 1,134 stars · 311 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 ICT-FinD-Lab/alphagen, 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 opening to clarify specialized role

    Why:

    CURRENT
    Automatic formulaic alpha generation with reinforcement learning.
    COPY-PASTE FIX
    AlphaGen is a specialized research framework and library for automatically discovering and generating novel, formulaic alpha factors for quantitative trading using reinforcement learning.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the MIT License.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    Set the repository homepage URL to the ACM DL link for the associated paper: `https://dl.acm.org/doi/10.1145/3485447.3512100`

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 ICT-FinD-Lab/alphagen
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. mementum/backtrader · recommended 1×
  4. pandas-dev/pandas · recommended 1×
  5. scikit-learn/scikit-learn · recommended 1×
  • CATEGORY QUERY
    How to automatically generate profitable stock trading signals using machine learning?
    you: not recommended
    AI recommended (in order):
    1. QuantConnect (QuantConnect/Lean)
    2. Zipline (quantopian/zipline)
    3. Backtrader (mementum/backtrader)
    4. pandas (pandas-dev/pandas)
    5. scikit-learn (scikit-learn/scikit-learn)
    6. TensorFlow (tensorflow/tensorflow)
    7. PyTorch (pytorch/pytorch)
    8. Keras (keras-team/keras)
    9. Alpha Vantage API
    10. Quandl
    11. Polygon.io

    AI recommended 11 alternatives but never named ICT-FinD-Lab/alphagen. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best reinforcement learning frameworks for algorithmic trading strategy discovery?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. Stable Baselines3 (SB3)
    3. OpenAI Gym/Farama Gymnasium
    4. TensorFlow Agents (TF-Agents)
    5. PyTorch-Lightning-RL
    6. Catalyst.RL
    7. ElegantRL

    AI recommended 7 alternatives but never named ICT-FinD-Lab/alphagen. 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 ICT-FinD-Lab/alphagen?
    pass
    AI named ICT-FinD-Lab/alphagen explicitly

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

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

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

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ICT-FinD-Lab/alphagen — 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