RRepoGEO

REPOGEO REPORT · LITE

ashleve/lightning-hydra-template

Default branch main · commit bddbc24b · scanned 6/26/2026, 7:46:45 AM

GitHub: 5,304 stars · 761 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)

3 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 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
  • highreadme#1
    Reposition README H1 to clarify project type

    Why:

    CURRENT
    # Lightning-Hydra-Template
    COPY-PASTE FIX
    # Lightning-Hydra-Template: A Starter Kit for Deep Learning Projects with PyTorch Lightning and Hydra
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Add a LICENSE file (e.g., MIT License) to the root of the repository.
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    COPY-PASTE FIX
    Set the homepage URL in the repository settings to https://github.com/ashleve/lightning-hydra-template (or a dedicated documentation site if one exists).

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
Lightning-AI/pytorch-lightning
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Lightning-AI/pytorch-lightning · recommended 1×
  2. keras-team/keras · recommended 1×
  3. fastai/fastai · recommended 1×
  4. huggingface/transformers · recommended 1×
  5. catalyst-team/catalyst · recommended 1×
  • CATEGORY QUERY
    How to quickly set up a new deep learning project with good structure and minimal boilerplate?
    you: not recommended
    AI recommended (in order):
    1. PyTorch Lightning (Lightning-AI/pytorch-lightning)
    2. Keras (keras-team/keras)
    3. Fast.ai (fastai/fastai)
    4. Hugging Face Transformers (huggingface/transformers)
    5. Catalyst (catalyst-team/catalyst)

    AI recommended 5 alternatives but never named ashleve/lightning-hydra-template. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a robust framework for managing deep learning experiments and ensuring configuration reproducibility.
    you: not recommended
    AI recommended (in order):
    1. MLflow
    2. Weights & Biases (W&B)
    3. Hydra
    4. ClearML
    5. Comet ML
    6. Sacred

    AI recommended 6 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 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?

  • 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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ashleve/lightning-hydra-template — 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