RRepoGEO

REPOGEO REPORT · LITE

intelligent-machine-learning/dlrover

Default branch master · commit 09d145c9 · scanned 5/24/2026, 12:31:57 PM

GitHub: 1,656 stars · 213 forks

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 intelligent-machine-learning/dlrover, 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
  • hightopics#1
    Add more specific topics to improve categorization

    Why:

    CURRENT
    distributed-training, hacktoberfest, k8s, llm-training
    COPY-PASTE FIX
    distributed-training, hacktoberfest, k8s, llm-training, kubernetes-native, fault-tolerant, auto-scaling, elastic-training, deep-learning-orchestration, pytorch-distributed
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://dlrover.github.io/ (or your project's official website)
  • lowreadme#3
    Clarify the project's license(s) in the README

    Why:

    COPY-PASTE FIX
    Add a section or line in the README, e.g., 'DLRover is licensed under [License Name(s) from your LICENSE file]. See the LICENSE file for details.'

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 intelligent-machine-learning/dlrover
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Kubeflow
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Kubeflow · recommended 2×
  2. Ray · recommended 2×
  3. Hugging Face Accelerate · recommended 2×
  4. Kubeflow Training Operator · recommended 1×
  5. KubeRay · recommended 1×
  • CATEGORY QUERY
    How to simplify distributed deep learning training for large AI models on Kubernetes?
    you: not recommended
    AI recommended (in order):
    1. Kubeflow
    2. Kubeflow Training Operator
    3. Ray
    4. KubeRay
    5. Hugging Face Accelerate
    6. PyTorch FSDP
    7. DeepSpeed
    8. Volcano

    AI recommended 8 alternatives but never named intelligent-machine-learning/dlrover. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a system for automated, fault-tolerant, and auto-scaling distributed deep learning jobs.
    you: not recommended
    AI recommended (in order):
    1. Kubeflow
    2. AWS SageMaker
    3. Azure Machine Learning
    4. Google Cloud AI Platform
    5. Ray
    6. MLflow
    7. Hugging Face Accelerate

    AI recommended 7 alternatives but never named intelligent-machine-learning/dlrover. 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 intelligent-machine-learning/dlrover?
    pass
    AI named intelligent-machine-learning/dlrover explicitly

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

  • If a team adopts intelligent-machine-learning/dlrover in production, what risks or prerequisites should they evaluate first?
    pass
    AI named intelligent-machine-learning/dlrover 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 intelligent-machine-learning/dlrover solve, and who is the primary audience?
    pass
    AI named intelligent-machine-learning/dlrover 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 intelligent-machine-learning/dlrover. 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/intelligent-machine-learning/dlrover.svg)](https://repogeo.com/en/r/intelligent-machine-learning/dlrover)
HTML
<a href="https://repogeo.com/en/r/intelligent-machine-learning/dlrover"><img src="https://repogeo.com/badge/intelligent-machine-learning/dlrover.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

intelligent-machine-learning/dlrover — 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