RRepoGEO

REPOGEO REPORT · LITE

ashleve/lightning-hydra-template

Default branch main · commit bddbc24b · scanned 5/15/2026, 3:27:20 PM

GitHub: 5,254 stars · 759 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 ashleve/lightning-hydra-template, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root, for example, with the MIT License text.
  • highreadme#2
    Strengthen README's opening sentence to emphasize template role for specific tools

    Why:

    CURRENT
    A clean template to kickstart your deep learning project 🚀⚡🔥
    COPY-PASTE FIX
    A clean, opinionated template to kickstart your **PyTorch Lightning and Hydra deep learning projects** 🚀⚡🔥
  • mediumhomepage#3
    Add the repository URL as the project homepage

    Why:

    COPY-PASTE FIX
    https://github.com/ashleve/lightning-hydra-template

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 ashleve/lightning-hydra-template
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PyTorch Lightning
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. PyTorch Lightning · recommended 1×
  2. Hydra · recommended 1×
  3. MLflow · recommended 1×
  4. Weights & Biases (W&B) · recommended 1×
  5. Poetry · recommended 1×
  • CATEGORY QUERY
    How to quickly set up a new deep learning project with a robust, modular structure?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning
    2. Hydra
    3. MLflow
    4. Weights & Biases (W&B)
    5. Poetry
    6. Cookiecutter Data Science

    AI recommended 6 alternatives but never named ashleve/lightning-hydra-template. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a template for reproducible deep learning experiments with flexible configuration management.
    you: not recommended
    AI recommended (in order):
    1. Hydra (facebookresearch/hydra)
    2. MLflow (mlflow/mlflow)
    3. Weights & Biases Sweeps (wandb/wandb)
    4. PyTorch Lightning (Lightning-AI/lightning)
    5. Sacred (IDSIA/sacred)
    6. ConfigArgParse (bwolf/ConfigArgParse)
    7. OmegaConf (omry/omegaconf)

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

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

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  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite