RRepoGEO

REPOGEO REPORT · LITE

rllm-org/rllm

Default branch main · commit 24eca958 · scanned 5/24/2026, 9:08:14 PM

GitHub: 5,561 stars · 570 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 rllm-org/rllm, 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
  • highabout#1
    Update repo description to specify LLM Agents

    Why:

    CURRENT
    Democratizing Reinforcement Learning for LLMs
    COPY-PASTE FIX
    Democratizing Reinforcement Learning for LLM Agents
  • highreadme#2
    Revise README's first paragraph to clarify Python and core value

    Why:

    CURRENT
    rLLM is an open-source framework for training AI agents with reinforcement learning. Swap in a tracked client, define a reward function, and let RL handle the rest — no matter what agent framework you use.
    COPY-PASTE FIX
    rLLM is an open-source Python framework for training AI agents with reinforcement learning. With minimal code changes, you can swap in a tracked client, define a reward function, and let RL handle the rest — no matter what agent framework you use.
  • mediumtopics#3
    Add specific agent framework topics

    Why:

    CURRENT
    agent-framework, agentic-workflow, coding-agent, distributed-training, llm-reasoning, llm-training, machine-learning, ml-infrastructure, ml-platform, reinforcement-learning, search-agent, swe-agent, tinker, verl
    COPY-PASTE FIX
    agent-framework, agentic-workflow, coding-agent, distributed-training, llm-reasoning, llm-training, machine-learning, ml-infrastructure, ml-platform, reinforcement-learning, search-agent, swe-agent, tinker, verl, langgraph, smolagent, strands, openai-agents-sdk, google-adk

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 rllm-org/rllm
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/trl
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/trl · recommended 1×
  2. OpenAI's API · recommended 1×
  3. deepmind/acme · recommended 1×
  4. DLR-RM/stable-baselines3 · recommended 1×
  5. langchain-ai/langchain · recommended 1×
  • CATEGORY QUERY
    How to apply reinforcement learning techniques to enhance the capabilities of my existing LLM agents?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face TRL (huggingface/trl)
    2. OpenAI's API
    3. Acme (deepmind/acme)
    4. Stable Baselines3 (DLR-RM/stable-baselines3)
    5. LangChain (langchain-ai/langchain)
    6. LlamaIndex (run-llama/llama_index)
    7. OpenAI GPT-4
    8. Anthropic Claude 3
    9. Gymnasium (Farama-Foundation/Gymnasium)
    10. RLlib (ray-project/ray)

    AI recommended 10 alternatives but never named rllm-org/rllm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a framework to train AI agents using reinforcement learning with minimal code changes.
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3
    2. RLlib
    3. CleanRL
    4. Tianshou
    5. Keras-RL
    6. Dopamine

    AI recommended 6 alternatives but never named rllm-org/rllm. This is the gap to close.

    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 rllm-org/rllm?
    pass
    AI named rllm-org/rllm explicitly

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

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

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

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