RRepoGEO

REPOGEO REPORT · LITE

minimaxir/automl-gs

Default branch master · commit 62773ce3 · scanned 5/27/2026, 1:57:12 AM

GitHub: 1,867 stars · 181 forks

AI VISIBILITY SCORE
28 /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
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 minimaxir/automl-gs, 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 to highlight zero-code, transparent Python code generation

    Why:

    CURRENT
    Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learning model plus native Python code pipelines allowing you to integrate that model into any prediction workflow. No black box: you can see *exactly* how the data is processed, how the model is constructed, and you can make tweaks as necessary.
    COPY-PASTE FIX
    automl-gs is a zero-code AutoML tool that generates a high-performing machine learning or deep learning model and native Python code pipelines directly from a CSV and a target field. It offers full transparency and local integration, unlike black-box solutions or those requiring specific cloud platforms or GUIs.
  • mediumtopics#2
    Add specific topics for zero-code ML and code generation

    Why:

    CURRENT
    automl, keras, machine-learning, python, tensorflow, xgboost
    COPY-PASTE FIX
    automl, keras, machine-learning, python, tensorflow, xgboost, zero-code-ml, code-generation, tabular-data
  • lowhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/minimaxir/automl-gs

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 minimaxir/automl-gs
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyCaret
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyCaret · recommended 1×
  2. TPOT (Tree-based Pipeline Optimization Tool) · recommended 1×
  3. H2O.ai AutoML · recommended 1×
  4. AutoGluon · recommended 1×
  5. scikit-learn · recommended 1×
  • CATEGORY QUERY
    How can I quickly generate machine learning models and Python code from a CSV dataset?
    you: not recommended
    AI recommended (in order):
    1. PyCaret
    2. TPOT (Tree-based Pipeline Optimization Tool)
    3. H2O.ai AutoML
    4. AutoGluon
    5. scikit-learn
    6. DataRobot
    7. Google Cloud AutoML Tables

    AI recommended 7 alternatives but never named minimaxir/automl-gs. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help automate machine learning model creation with transparent, customizable Python pipelines?
    you: not recommended
    AI recommended (in order):
    1. Scikit-learn Pipelines
    2. MLflow
    3. Kedro
    4. Prefect
    5. DVC
    6. Metaflow

    AI recommended 6 alternatives but never named minimaxir/automl-gs. 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 minimaxir/automl-gs?
    pass
    AI did not name minimaxir/automl-gs — 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 minimaxir/automl-gs in production, what risks or prerequisites should they evaluate first?
    pass
    AI named minimaxir/automl-gs 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 minimaxir/automl-gs solve, and who is the primary audience?
    pass
    AI named minimaxir/automl-gs explicitly

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

Embed your GEO score

Drop this badge into the README of minimaxir/automl-gs. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/minimaxir/automl-gs.svg)](https://repogeo.com/en/r/minimaxir/automl-gs)
HTML
<a href="https://repogeo.com/en/r/minimaxir/automl-gs"><img src="https://repogeo.com/badge/minimaxir/automl-gs.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

minimaxir/automl-gs — 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