REPOGEO REPORT · LITE

linyiLYi/street-fighter-ai

Default branch master · commit 78cb661e · scanned 5/23/2026, 2:32:35 PM

GitHub: 6,527 stars · 1,381 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

22 /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

1 / 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 linyiLYi/street-fighter-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.

OVERALL DIRECTION

highreadme#1

Reposition README H1 and first sentence to clarify project type

Why:

CURRENT

# SFighterAI

This project is an AI agent trained using deep reinforcement learning to beat the final boss in the game "Street Fighter II: Special Champion Edition".

COPY-PASTE FIX

# SFighterAI: Deep Reinforcement Learning AI Agent for Street Fighter II

This project demonstrates an AI agent trained using deep reinforcement learning to beat the final boss in the game "Street Fighter II: Special Champion Edition".

hightopics#2

Add relevant topics to the repository

Why:

COPY-PASTE FIX

deep-reinforcement-learning, ai-agent, game-ai, street-fighter, retro-gaming, openai-gym-retro, stable-baselines3, python, pixel-data

mediumhomepage#3
Add a homepage URL to the repository settings
Why:
COPY-PASTE FIX
```
https://github.com/linyiLYi/street-fighter-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.

Recall

0 / 2

0% of queries surface linyiLYi/street-fighter-ai

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

ray-project/ray

Recommended in 3 of 2 queries

COMPETITOR LEADERBOARD

ray-project/ray · recommended 3×
DLR-RM/stable-baselines3 · recommended 2×
tensorflow/agents · recommended 2×
openai/gym · recommended 1×
Lightning-AI/lightning · recommended 1×

CATEGORY QUERY
How to develop an AI agent using deep reinforcement learning for classic arcade fighting games?
you: not recommended
AI recommended (in order):
1. OpenAI Gym (openai/gym)
2. Stable Baselines3 (DLR-RM/stable-baselines3)
3. RLlib (ray-project/ray)
4. TensorFlow Agents (tensorflow/agents)
5. PyTorch Lightning (Lightning-AI/lightning)
6. Keras-RL2 (keras-rl/keras-rl2)
7. Gym Retro (openai/retro)
AI recommended 7 alternatives but never named linyiLYi/street-fighter-ai. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for Python examples of training game AI agents directly from screen pixel data.
you: not recommended
AI recommended (in order):
1. Gymnasium (Farama-Foundation/Gymnasium)
2. Stable Baselines3 (DLR-RM/stable-baselines3)
3. PyTorch (pytorch/pytorch)
4. torchvision (pytorch/vision)
5. torchaudio (pytorch/audio)
6. TensorFlow (tensorflow/tensorflow)
7. Keras (keras-team/keras)
8. tf-agents (tensorflow/agents)
9. Minigrid (Farama-Foundation/Minigrid)
10. RLlib (ray-project/ray)
11. Ray (ray-project/ray)
12. ViZDoom (mwydmuch/ViZDoom)
AI recommended 12 alternatives but never named linyiLYi/street-fighter-ai. 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 linyiLYi/street-fighter-ai?
pass
AI did not name linyiLYi/street-fighter-ai — 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 linyiLYi/street-fighter-ai in production, what risks or prerequisites should they evaluate first?
pass
AI named linyiLYi/street-fighter-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/street-fighter-ai solve, and who is the primary audience?
pass
AI did not name linyiLYi/street-fighter-ai — 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?

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MARKDOWN (README)

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linyiLYi/street-fighter-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