RRepoGEO

REPOGEO REPORT · LITE

PeterGriffinJin/Search-R1

Default branch main · commit 598e61bd · scanned 5/27/2026, 10:19:00 AM

GitHub: 4,791 stars · 428 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 PeterGriffinJin/Search-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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Refine the 'About' description for clearer categorization

    Why:

    CURRENT
    Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL
    COPY-PASTE FIX
    Search-R1 is an open-source, scalable reinforcement learning (RL) framework for training LLMs to reason and use search engines. It's an alternative to DeepSeek-R1 and OpenAI DeepResearch.
  • mediumcomparison#2
    Add a dedicated 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Search-R1 differentiates itself by providing a fully open-source RL training pipeline for reasoning-and-searching interleaved LLMs. While inspired by DeepSeek-R1(-Zero), we focus on integrating diverse search engine access. Unlike proprietary solutions such as OpenAI DeepResearch, Search-R1 offers a transparent and extensible framework for research and development. We also provide support for various RL methods (PPO, GRPO, reinforce) and LLMs (llama3, Qwen2.5), offering flexibility beyond many existing tools.

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 PeterGriffinJin/Search-R1
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Hugging Face Transformers Agents · recommended 1×
  4. OpenAI Function Calling and Assistants API · recommended 1×
  5. Google Vertex AI Agent Builder · recommended 1×
  • CATEGORY QUERY
    How to train large language models to reason and effectively use search tools?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Hugging Face Transformers Agents
    4. OpenAI Function Calling and Assistants API
    5. Google Vertex AI Agent Builder
    6. Microsoft Semantic Kernel
    7. AutoGPT
    8. BabyAGI

    AI recommended 8 alternatives but never named PeterGriffinJin/Search-R1. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking an open-source reinforcement learning framework for LLM reasoning and search engine integration.
    you: not recommended
    AI recommended (in order):
    1. Hugging Face Transformers
    2. PEFT
    3. Hugging Face TRL
    4. DeepSpeed-Chat
    5. Ray RLlib
    6. Stable Baselines3
    7. OpenAI Gym
    8. Farama Gymnasium
    9. CleanRL
    10. Keras-RL2

    AI recommended 10 alternatives but never named PeterGriffinJin/Search-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 PeterGriffinJin/Search-R1?
    pass
    AI named PeterGriffinJin/Search-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 PeterGriffinJin/Search-R1 in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PeterGriffinJin/Search-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 PeterGriffinJin/Search-R1 solve, and who is the primary audience?
    pass
    AI named PeterGriffinJin/Search-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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PeterGriffinJin/Search-R1 — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite