RRepoGEO

REPOGEO REPORT · LITE

openreasoner/openr

Default branch main · commit 54ae004c · scanned 5/16/2026, 12:47:50 AM

GitHub: 1,842 stars · 130 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 openreasoner/openr, 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
  • highreadme#1
    Add a disambiguation note in the README's introduction

    Why:

    CURRENT
    The current README does not explicitly distinguish this project from other projects named "OpenR".
    COPY-PASTE FIX
    Insert the following sentence immediately after the main H1 title: "Note: This OpenR project is specifically designed for advanced reasoning with Large Language Models and is distinct from any networking projects that may share a similar name."
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, large-language-models, reasoning, ai, artificial-intelligence, nlp, natural-language-processing, framework, deep-learning, agent, knowledge-graph
  • mediumreadme#3
    Briefly contextualize OpenR's unique contribution within the LLM reasoning ecosystem

    Why:

    CURRENT
    The README's current introduction focuses on what OpenR is.
    COPY-PASTE FIX
    In the first descriptive paragraph, add a sentence like: "Unlike general-purpose LLM orchestration tools, OpenR focuses on enabling sophisticated, multi-step reasoning processes and knowledge inference, pushing the boundaries of what LLMs can achieve in complex problem-solving."

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 openreasoner/openr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. FAISS · recommended 1×
  4. Pinecone · recommended 1×
  5. Weaviate · recommended 1×
  • CATEGORY QUERY
    How can I improve the advanced reasoning capabilities of large language models for complex tasks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. FAISS
    4. Pinecone
    5. Weaviate
    6. Hugging Face Transformers
    7. LoRA
    8. Prolog
    9. Wolfram Alpha APIs
    10. Auto-GPT
    11. BabyAGI

    AI recommended 11 alternatives but never named openreasoner/openr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source frameworks are available for developing sophisticated reasoning systems with LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. DSPy

    AI recommended 5 alternatives but never named openreasoner/openr. 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 openreasoner/openr?
    pass
    AI named openreasoner/openr explicitly

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

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

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

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  • Brand-free category queries5 vs 2 in Lite
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