RRepoGEO

REPOGEO REPORT · LITE

AgentR1/Agent-R1

Default branch main · commit 898c36d6 · scanned 5/26/2026, 12:18:24 AM

GitHub: 1,433 stars · 94 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 AgentR1/Agent-R1, 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 more specific topics to clarify the project's niche

    Why:

    CURRENT
    agent, agentic-rl, llm
    COPY-PASTE FIX
    agent, agentic-rl, llm, llm-agents, llm-framework, autonomous-agents
  • highreadme#2
    Add a concise tagline immediately after the main README title

    Why:

    CURRENT
    The README currently jumps from the H1 title directly to badges and then a 'News' section, without an immediate descriptive tagline.
    COPY-PASTE FIX
    Add the following line right after the H1:
`<p align="center">A comprehensive framework for building and training powerful LLM agents using end-to-end reinforcement learning.</p>`
  • mediumhomepage#3
    Set the repository homepage URL

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://agentr1.github.io/Agent-R1/

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 AgentR1/Agent-R1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. deepmind/acme · recommended 2×
  3. huggingface/transformers · recommended 1×
  4. huggingface/trl · recommended 1×
  5. vwxyzjn/cleanrl · recommended 1×
  • CATEGORY QUERY
    How to effectively train large language model agents using end-to-end reinforcement learning?
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers (huggingface/transformers)
    2. TRL library (huggingface/trl)
    3. Ray RLlib (ray-project/ray)
    4. CleanRL (vwxyzjn/cleanrl)
    5. DreamerV3
    6. DreamerV2
    7. PlaNet
    8. AlphaZero
    9. MuZero
    10. PyTorch (pytorch/pytorch)
    11. TensorFlow Agents (TF-Agents) (tensorflow/agents)
    12. DeepMind's Acme (deepmind/acme)

    AI recommended 12 alternatives but never named AgentR1/Agent-R1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Frameworks for developing general autonomous agents with agentic reinforcement learning capabilities?
    you: not recommended
    AI recommended (in order):
    1. Farama Gymnasium (Farama-Foundation/Gymnasium)
    2. Stable Baselines3 (DLR-RM/stable-baselines3)
    3. DeepMind's Acme (deepmind/acme)
    4. RLlib (ray-project/ray)
    5. Minigrid (Farama-Foundation/Minigrid)
    6. PettingZoo (Farama-Foundation/PettingZoo)
    7. Unity ML-Agents (Unity-Technologies/ml-agents)

    AI recommended 7 alternatives but never named AgentR1/Agent-R1. 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 AgentR1/Agent-R1?
    pass
    AI named AgentR1/Agent-R1 explicitly

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

  • If a team adopts AgentR1/Agent-R1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AgentR1/Agent-R1 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 AgentR1/Agent-R1 solve, and who is the primary audience?
    pass
    AI named AgentR1/Agent-R1 explicitly

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

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AgentR1/Agent-R1 — 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