REPOGEO REPORT · LITE
linyiLYi/snake-ai
Default branch master · commit a067bfc1 · scanned 7/1/2026, 12:52:50 PM
GitHub: 1,782 stars · 398 forks
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.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
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 linyiLYi/snake-ai, 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.
- hightopics#1Add relevant topics to the repository
Why:
COPY-PASTE FIXdeep-reinforcement-learning, game-ai, snake-game, python, machine-learning, neural-networks, mlp, cnn
- highreadme#2Reposition the README's H1 and opening sentence to clarify project type
Why:
CURRENT# SnakeAI [简体中文](README_CN.md) | English | [日本語](README_JA.md) This project contains the program scripts for the classic game "Snake" and an artificial intelligence agent that can play the game automatically. The intelligent agent is trained using deep reinforcement learning and includes two versions: an agent based on a Multi-Layer Perceptron (MLP) and an agent based on a Convolution Neural Network (CNN), with the latter having a higher average game score.
COPY-PASTE FIX# SnakeAI: Deep Reinforcement Learning Agent for the Classic Snake Game [简体中文](README_CN.md) | English | [日本語](README_JA.md) This project demonstrates an artificial intelligence agent that automatically plays the classic game "Snake", primarily for learning and experimentation with deep reinforcement learning. The intelligent agent is trained using deep reinforcement learning and includes two versions: an agent based on a Multi-Layer Perceptron (MLP) and an agent based on a Convolution Neural Network (CNN), with the latter having a higher average game score.
- mediumhomepage#3Add a homepage URL to the repository metadata
Why:
COPY-PASTE FIXhttps://github.com/linyiLYi/snake-ai
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.
- openai/gym · recommended 1×
- Farama-Foundation/Gymnasium · recommended 1×
- pygame/pygame · recommended 1×
- gym_flappy_bird · recommended 1×
- Farama-Foundation/Minigrid · recommended 1×
- CATEGORY QUERYWhat are good deep reinforcement learning projects for training agents in simple game environments?you: not recommendedAI recommended (in order):
- OpenAI Gym (openai/gym)
- Gymnasium (Farama-Foundation/Gymnasium)
- PyGame (pygame/pygame)
- gym_flappy_bird
- MiniGrid (Farama-Foundation/Minigrid)
- PyGame Learning Environment (ntasfi/PyGame-Learning-Environment)
- DeepMind Lab (deepmind/lab)
AI recommended 7 alternatives but never named linyiLYi/snake-ai. This is the gap to close.
Show full AI answer
- CATEGORY QUERYHow can I create an AI player for classic arcade games using neural networks?you: not recommendedAI recommended (in order):
- OpenAI Gym
- Stable Baselines3
- Keras-RL2
- TensorFlow
- Keras
- PyTorch-Lightning
- PyTorch
- RLlib
- Ray
- Acme
- JAX
AI recommended 11 alternatives but never named linyiLYi/snake-ai. 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 linyiLYi/snake-ai?passAI named linyiLYi/snake-ai explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts linyiLYi/snake-ai in production, what risks or prerequisites should they evaluate first?passAI named linyiLYi/snake-ai 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 linyiLYi/snake-ai solve, and who is the primary audience?passAI named linyiLYi/snake-ai explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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linyiLYi/snake-ai — 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