REPOGEO REPORT · LITE
hardmaru/slimevolleygym
Default branch master · commit 8ac22434 · scanned 6/16/2026, 10:53:23 PM
GitHub: 785 stars · 124 forks
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 hardmaru/slimevolleygym, 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
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README opening to highlight multi-agent and GPU acceleration
Why:
CURRENTSlimeVolleyGym is a simple gym environment for testing single and multi-agent reinforcement learning algorithms.
COPY-PASTE FIXSlimeVolleyGym is a simple, fast OpenAI Gym environment designed for testing single and multi-agent reinforcement learning algorithms, including those leveraging GPU-accelerated neuroevolution via EvoJAX.
- mediumreadme#2Add a dedicated 'Notes on Libraries' section to the README
Why:
CURRENTThe pre-trained PPO models were trained using stable-baselines v2.10, *not* stable-baselines3.
COPY-PASTE FIX## Notes on Libraries - The pre-trained PPO models were trained using stable-baselines v2.10, *not* stable-baselines3.
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.
- MuJoCo · recommended 2×
- oxwhirl/smac · recommended 1×
- openai/multiagent-particle-envs · recommended 1×
- PettingZoo/PettingZoo · recommended 1×
- PKU-MARL/MAgent · recommended 1×
- CATEGORY QUERYWhat are good gym environments for testing multi-agent reinforcement learning algorithms?you: not recommendedAI recommended (in order):
- SMAC (StarCraft Multi-Agent Challenge) (oxwhirl/smac)
- Multi-Agent Particle Environment (MPE) (openai/multiagent-particle-envs)
- PettingZoo (PettingZoo/PettingZoo)
- MAgent (PKU-MARL/MAgent)
- Google Research Football (google-research/football)
- Pommerman (MultiAgentLearning/Pommerman)
- Overcooked-AI (HumanCompatibleAI/overcooked_ai)
AI recommended 7 alternatives but never named hardmaru/slimevolleygym. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhich gym environments support GPU-accelerated training for reinforcement learning research?you: not recommendedAI recommended (in order):
- Isaac Gym
- Isaac Sim
- Brax
- MuJoCo
- DM-Lab
- Gymnasium
- OpenAI Gym
- PyTorch
- TensorFlow
- Unity ML-Agents
- Unity
- PhysX
- RoboStack
- ROS
- Gazebo
- MuJoCo
- PyBullet
AI recommended 17 alternatives but never named hardmaru/slimevolleygym. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
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 hardmaru/slimevolleygym?passAI did not name hardmaru/slimevolleygym — 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 hardmaru/slimevolleygym in production, what risks or prerequisites should they evaluate first?passAI named hardmaru/slimevolleygym 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 hardmaru/slimevolleygym solve, and who is the primary audience?passAI named hardmaru/slimevolleygym explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
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hardmaru/slimevolleygym — 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