RRepoGEO

REPOGEO REPORT · LITE

williamFalcon/DeepRLHacks

Default branch master · commit c111306a · scanned 5/22/2026, 1:43:16 AM

GitHub: 1,124 stars · 120 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
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 fail
Objective metadata checks
AI knows your name
3 / 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 williamFalcon/DeepRLHacks, 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.

OVERALL DIRECTION
  • highreadme#1
    Reposition the README's opening to clearly state its purpose

    Why:

    CURRENT
    # DeepRLHacks
From a talk given by John Schulman titled "The Nuts and Bolts of Deep RL Research" (Aug 2017)
These are tricks written down while attending summer Deep RL Bootcamp at UC Berkeley.
    COPY-PASTE FIX
    # DeepRLHacks: Practical Tips for Debugging and Optimizing Deep Reinforcement Learning
This repository provides actionable "hacks" and best practices for training robust Deep Reinforcement Learning (DRL) systems, compiled from John Schulman's "The Nuts and Bolts of Deep RL Research" talk at the Aug 2017 Deep RL Bootcamp.
  • mediumlicense#2
    Add a LICENSE file to clarify usage terms

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root and populate it with the text of a suitable open-source license, such as the MIT License, to clearly define usage terms.

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 williamFalcon/DeepRLHacks
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
wandb/wandb
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. wandb/wandb · recommended 2×
  2. ray-project/ray · recommended 2×
  3. gymnasium/gymnasium · recommended 1×
  4. openai/gym · recommended 1×
  5. tensorflow/tensorboard · recommended 1×
  • CATEGORY QUERY
    Seeking practical tips to debug and optimize deep reinforcement learning agent performance.
    you: not recommended
    AI recommended (in order):
    1. Gymnasium (gymnasium/gymnasium)
    2. OpenAI Gym (openai/gym)
    3. TensorBoard (tensorflow/tensorboard)
    4. Weights & Biases (W&B) (wandb/wandb)
    5. MLflow (mlflow/mlflow)
    6. OpenCV (opencv/opencv)
    7. Matplotlib (matplotlib/matplotlib)
    8. pdb
    9. Jupyter Notebooks (jupyter/notebook)
    10. pytest (pytest-dev/pytest)
    11. Optuna (optuna/optuna)
    12. Ray Tune (ray-project/ray)
    13. Weights & Biases Sweeps (wandb/wandb)
    14. PyTorch (pytorch/pytorch)
    15. TensorFlow (tensorflow/tensorflow)
    16. JAX (google/jax)
    17. Stable Baselines3 (DLR-RM/stable-baselines3)
    18. RLlib (ray-project/ray)
    19. CleanRL (vwxyzjn/cleanrl)

    AI recommended 19 alternatives but never named williamFalcon/DeepRLHacks. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are best practices for training robust reinforcement learning models effectively?
    you: not recommended
    AI recommended (in order):
    1. Rainbow DQN
    2. PPO
    3. Stable Baselines3
    4. RLlib
    5. SAC
    6. Isaac Gym
    7. Albumentations
    8. PyTorch
    9. TensorFlow
    10. HER
    11. DDPG
    12. Gymnasium
    13. PETS
    14. PlaNet
    15. Dreamer
    16. Conservative Q-Learning (CQL)
    17. Implicit Q-Learning (IQL)
    18. D4RL

    AI recommended 18 alternatives but never named williamFalcon/DeepRLHacks. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 williamFalcon/DeepRLHacks?
    pass
    AI named williamFalcon/DeepRLHacks explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts williamFalcon/DeepRLHacks in production, what risks or prerequisites should they evaluate first?
    pass
    AI named williamFalcon/DeepRLHacks 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 williamFalcon/DeepRLHacks solve, and who is the primary audience?
    pass
    AI named williamFalcon/DeepRLHacks explicitly

    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 williamFalcon/DeepRLHacks. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/williamFalcon/DeepRLHacks.svg)](https://repogeo.com/en/r/williamFalcon/DeepRLHacks)
HTML
<a href="https://repogeo.com/en/r/williamFalcon/DeepRLHacks"><img src="https://repogeo.com/badge/williamFalcon/DeepRLHacks.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

williamFalcon/DeepRLHacks — 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