RRepoGEO

REPOGEO REPORT · LITE

KhoomeiK/LlamaGym

Default branch main · commit 92d7827b · scanned 5/15/2026, 3:53:04 AM

GitHub: 1,251 stars · 63 forks

AI VISIBILITY SCORE
35 /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
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 KhoomeiK/LlamaGym, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-agents, reinforcement-learning, online-learning, gym-environments, fine-tuning, python, machine-learning
  • highreadme#2
    Reposition the README's opening to highlight the 'Gym for LLM agents' differentiator

    Why:

    CURRENT
    "Agents" originated in reinforcement learning, where they learn by interacting with an environment and receiving a reward signal. However, LLM-based agents today do not learn online (i.e. continuously in real time) via reinforcement.
    COPY-PASTE FIX
    LlamaGym provides an OpenAI Gym-like environment and API for training LLM agents with online reinforcement learning. It simplifies the process of fine-tuning LLM agents by handling conversation context, reward assignment, and PPO setup, allowing you to quickly iterate on agent prompting and hyperparameters.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://reworkd.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 KhoomeiK/LlamaGym
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Hugging Face Transformers
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Hugging Face Transformers · recommended 1×
  2. TRL (Transformer Reinforcement Learning) · recommended 1×
  3. Ray RLlib · recommended 1×
  4. DeepMind's Acme · recommended 1×
  5. JAX/Flax · recommended 1×
  • CATEGORY QUERY
    How to fine-tune large language models using online reinforcement learning?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. TRL (Transformer Reinforcement Learning)
    3. Ray RLlib
    4. DeepMind's Acme
    5. JAX/Flax
    6. PyTorch
    7. Hugging Face Accelerate
    8. OpenAI Gym / Farama Foundation Gymnasium
    9. Stable Baselines3

    AI recommended 9 alternatives but never named KhoomeiK/LlamaGym. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools simplify continuous reinforcement learning for LLM agent development?
    you: not recommended
    AI recommended (in order):
    1. TRL (huggingface/trl)
    2. DeepSpeed-Chat (microsoft/DeepSpeed)
    3. Ray RLlib (ray-project/ray)
    4. Stable Baselines3 (DLR-RM/stable-baselines3)
    5. OpenAI Gym (openai/gym)
    6. Farama Gymnasium (Farama-Foundation/Gymnasium)
    7. PyTorch (pytorch/pytorch)
    8. TensorFlow (tensorflow/tensorflow)

    AI recommended 8 alternatives but never named KhoomeiK/LlamaGym. 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 KhoomeiK/LlamaGym?
    pass
    AI named KhoomeiK/LlamaGym explicitly

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

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

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

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KhoomeiK/LlamaGym — 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