RRepoGEO

REPOGEO REPORT · LITE

NeuronDance/DeepRL

Default branch master · commit 8342ea71 · scanned 5/23/2026, 3:52:48 PM

GitHub: 2,561 stars · 598 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
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 NeuronDance/DeepRL, 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
    Add a concise English positioning statement to the README's opening

    Why:

    CURRENT
    The current README starts with a Chinese title and a long historical overview.
    COPY-PASTE FIX
    This repository, created by the DeepRL-Lab, provides a comprehensive open-source lab environment and platform for implementing and experimenting with Deep Reinforcement Learning (DRL) algorithms. It aims to guide researchers, students, and enthusiasts through practical DRL concepts and techniques.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    deep-reinforcement-learning, reinforcement-learning, drl, machine-learning, artificial-intelligence, pytorch, algorithms, lab-environment
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://github.com/NeuronDance/DeepRL

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 NeuronDance/DeepRL
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Coursera
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Coursera · recommended 1×
  2. DeepLearning.AI · recommended 1×
  3. tensorflow/tensorflow · recommended 1×
  4. keras-team/keras · recommended 1×
  5. openai/spinningup · recommended 1×
  • CATEGORY QUERY
    What are good platforms for learning deep reinforcement learning concepts and techniques?
    you: not recommended
    AI recommended (in order):
    1. Coursera
    2. DeepLearning.AI
    3. TensorFlow (tensorflow/tensorflow)
    4. Keras (keras-team/keras)
    5. OpenAI Spinning Up in Deep RL (openai/spinningup)
    6. PyTorch (pytorch/pytorch)
    7. edX
    8. UC Berkeley
    9. NumPy (numpy/numpy)
    10. Udemy
    11. freeCodeCamp.org
    12. RL-Lab.com
    13. Sutton & Barto's "Reinforcement Learning: An Introduction"

    AI recommended 13 alternatives but never named NeuronDance/DeepRL. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source lab environment to experiment with deep reinforcement learning algorithms.
    you: not recommended
    AI recommended (in order):
    1. Gymnasium (Farama-Foundation/Gymnasium)
    2. DeepMind Lab (deepmind/lab)
    3. Unity ML-Agents (Unity-Technologies/ml-agents)
    4. Minigrid (Farama-Foundation/Minigrid)
    5. MetaWorld (rlworkgroup/metaworld)
    6. PyBullet (bulletphysics/pybullet)

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

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

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NeuronDance/DeepRL — 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