REPOGEO REPORT · LITE

nikhilbarhate99/PPO-PyTorch

Default branch master · commit 728cce83 · scanned 6/28/2026, 9:41:35 AM

GitHub: 2,362 stars · 425 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

28 /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

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 nikhilbarhate99/PPO-PyTorch, 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 core purpose statement in README

Why:

COPY-PASTE FIX

# PPO-PyTorch

This repository offers a minimal PyTorch implementation of Proximal Policy Optimization (PPO) with clipped objective, primarily designed for beginners in Reinforcement Learning to understand the PPO algorithm. It includes a convenient Google Colab notebook for hands-on learning.

mediumhomepage#2
Add a homepage URL pointing to the Colab notebook
Why:
CURRENT
```
(none)
```
COPY-PASTE FIX
```
https://colab.research.google.com/github/nikhilbarhate99/PPO-PyTorch/blob/master/PPO_colab.ipynb
```
lowtopics#3
Correct typo in existing topic `pytorch-implmention`
Why:
CURRENT
```
pytorch-implmention
```
COPY-PASTE FIX
```
pytorch-implementation
```

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 nikhilbarhate99/PPO-PyTorch

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

CleanRL

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

CleanRL · recommended 2×
Stable Baselines3 · recommended 2×
RLlib · recommended 2×
pytorch/examples · recommended 1×
Farama-Foundation/Minigrid · recommended 1×

CATEGORY QUERY
How to implement Proximal Policy Optimization in PyTorch for learning reinforcement learning basics?
you: not recommended
AI recommended (in order):
1. CleanRL
2. Stable Baselines3
3. RLlib
4. PyTorch-RL (pytorch/examples)
5. Minigrid-PPO (Farama-Foundation/Minigrid)
AI recommended 5 alternatives but never named nikhilbarhate99/PPO-PyTorch. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What are good PyTorch libraries for applying PPO to solve OpenAI Gym reinforcement learning tasks?
you: not recommended
AI recommended (in order):
1. RLlib
2. Stable Baselines3
3. CleanRL
4. Tianshou
5. Catalyst.RL
AI recommended 5 alternatives but never named nikhilbarhate99/PPO-PyTorch. 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 nikhilbarhate99/PPO-PyTorch?
pass
AI named nikhilbarhate99/PPO-PyTorch explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts nikhilbarhate99/PPO-PyTorch in production, what risks or prerequisites should they evaluate first?
pass
AI named nikhilbarhate99/PPO-PyTorch 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 nikhilbarhate99/PPO-PyTorch solve, and who is the primary audience?
pass
AI did not name nikhilbarhate99/PPO-PyTorch — 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?

Embed your GEO score

Drop this badge into the README of nikhilbarhate99/PPO-PyTorch. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)

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nikhilbarhate99/PPO-PyTorch — 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