REPOGEO REPORT · LITE

vwxyzjn/cleanrl

Default branch master · commit fe8d8a03 · scanned 6/26/2026, 11:56:51 PM

GitHub: 10,019 stars · 1,109 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)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

83 /100

Healthy

Category recall

2 / 2

Avg rank #2.0 when recommended

Rule findings

2 pass · 0 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 vwxyzjn/cleanrl, 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

Explicitly state CleanRL's core differentiator in the README's opening

Why:

CURRENT

CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementation with research-friendly features.

COPY-PASTE FIX

CleanRL is a Deep Reinforcement Learning library that provides high-quality single-file implementations with research-friendly features. Its core differentiator is offering highly readable, self-contained, single-file versions of popular DRL algorithms, making it ideal for learning, debugging, and reproducibility without the complexity of modular libraries.

mediumreadme#2

Clarify the project's license(s) in the README

Why:

COPY-PASTE FIX

CleanRL is distributed under [Specify License Name(s) here, e.g., 'a custom license combining X and Y'] for clarity.

lowtopics#3

Add topics emphasizing the educational and research-friendly aspects

Why:

CURRENT

a2c, actor-critic, advantage-actor-critic, ale, atari, deep-learning, deep-reinforcement-learning, gym, machine-learning, phasic-policy-gradient, ppo, proximal-policy-optimization, python, pytorch, reinforcement-learning, wandb

COPY-PASTE FIX

a2c, actor-critic, advantage-actor-critic, ale, atari, deep-learning, deep-reinforcement-learning, drl-education, gym, machine-learning, phasic-policy-gradient, ppo, proximal-policy-optimization, python, pytorch, reinforcement-learning, research-friendly, wandb

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

2 / 2

100% of queries surface vwxyzjn/cleanrl

Avg rank

#2.0

Lower is better. #1 = top recommendation.

Share of voice

15%

Of all named tools, what % are you?

Top rival

DLR-RM/stable-baselines3

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

DLR-RM/stable-baselines3 · recommended 1×
ray-project/ray · recommended 1×
thu-ml/tianshou · recommended 1×
Farama-Foundation/Minigrid · recommended 1×
pytorch/pytorch · recommended 1×

CATEGORY QUERY
What are good Python libraries for learning deep reinforcement learning algorithm implementations clearly?
you: #1
AI recommended (in order):
1. CleanRL (cleanrl/cleanrl) ← you
2. Stable Baselines3 (DLR-RM/stable-baselines3)
3. RLlib (ray-project/ray)
4. Tianshou (thu-ml/tianshou)
5. Minigrid (Farama-Foundation/Minigrid)
6. PyTorch (pytorch/pytorch)
7. TensorFlow (tensorflow/tensorflow)
Show full AI answer
CATEGORY QUERY
Looking for a Python deep reinforcement learning framework to quickly benchmark various algorithms.
you: #3
AI recommended (in order):
1. RLlib
2. Stable Baselines3
3. CleanRL ← you
4. Tianshou
5. Acme
6. Keras-RL
Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

Metadata completeness
pass
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 vwxyzjn/cleanrl?
pass
AI did not name vwxyzjn/cleanrl — 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 vwxyzjn/cleanrl in production, what risks or prerequisites should they evaluate first?
pass
AI named vwxyzjn/cleanrl 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 vwxyzjn/cleanrl solve, and who is the primary audience?
pass
AI named vwxyzjn/cleanrl 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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MARKDOWN (README)

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HTML

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite