RRepoGEO

REPOGEO REPORT · LITE

uoe-agents/epymarl

Default branch main · commit cbc38c09 · scanned 6/9/2026, 4:42:01 AM

GitHub: 721 stars · 189 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 uoe-agents/epymarl, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    multi-agent-reinforcement-learning, marl, reinforcement-learning, deep-learning, pytorch, gymnasium, pettingzoo, smac, smacv2, research-framework
  • mediumreadme#2
    Strengthen the README's opening statement for better category alignment

    Why:

    CURRENT
    # Extended Python MARL framework - EPyMARL
    COPY-PASTE FIX
    # EPyMARL: An Extended PyTorch Framework for Multi-Agent Reinforcement Learning Research
  • lowhomepage#3
    Add the project's blog post URL as the repository homepage

    Why:

    COPY-PASTE FIX
    https://agents.inf.ed.ac.uk/blog/epymarl/

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 uoe-agents/epymarl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Farama-Foundation/PettingZoo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Farama-Foundation/PettingZoo · recommended 1×
  2. ray-project/ray · recommended 1×
  3. deepmind/open_spiel · recommended 1×
  4. Farama-Foundation/MARL-Baselines · recommended 1×
  5. pytorch/rl · recommended 1×
  • CATEGORY QUERY
    Seeking a Python framework for multi-agent reinforcement learning experiments with diverse environments.
    you: not recommended
    AI recommended (in order):
    1. PettingZoo (Farama-Foundation/PettingZoo)
    2. RLlib (ray-project/ray)
    3. OpenSpiel (deepmind/open_spiel)
    4. MARL-Baselines (Farama-Foundation/MARL-Baselines)
    5. TorchRL (pytorch/rl)

    AI recommended 5 alternatives but never named uoe-agents/epymarl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are robust multi-agent reinforcement learning frameworks supporting Gymnasium and diverse algorithms?
    you: not recommended
    AI recommended (in order):
    1. PettingZoo
    2. RLlib
    3. OpenSpiel
    4. MARL-Baselines
    5. Stable Baselines3

    AI recommended 5 alternatives but never named uoe-agents/epymarl. 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 uoe-agents/epymarl?
    pass
    AI named uoe-agents/epymarl explicitly

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

  • If a team adopts uoe-agents/epymarl in production, what risks or prerequisites should they evaluate first?
    pass
    AI named uoe-agents/epymarl 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 uoe-agents/epymarl solve, and who is the primary audience?
    pass
    AI named uoe-agents/epymarl explicitly

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

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uoe-agents/epymarl — 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