RRepoGEO

REPOGEO REPORT · LITE

openreasoner/openr

Default branch main · commit 54ae004c · scanned 6/26/2026, 8:17:50 PM

GitHub: 1,849 stars · 132 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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
  • hightopics#1
    Add specific, relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    llm, reasoning, large-language-models, nlp, artificial-intelligence, framework, python, ai-framework
  • highreadme#2
    Add a concise, explicit introductory sentence or paragraph immediately after the main title in the README

    Why:

    COPY-PASTE FIX
    OpenR is a cutting-edge open-source framework designed specifically to enhance the advanced reasoning capabilities of Large Language Models (LLMs) for complex problem-solving.
  • mediumreadme#3
    Add a dedicated 'Key Features' or 'Why OpenR?' section early in the README

    Why:

    COPY-PASTE FIX
    Add a section titled 'Key Features' or 'Why OpenR?' that outlines specific benefits like modularity for LLM reasoning, support for various reasoning paradigms, or ease of integration with LLM applications.

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. AutoGPT · recommended 2×
  4. GSM8K · recommended 1×
  5. MATH · recommended 1×
  • CATEGORY QUERY
    How can I enhance large language model capabilities for complex reasoning tasks?
    you: not recommended
    AI recommended (in order):
    1. GSM8K
    2. MATH
    3. Alpaca-CoT
    4. LangChain
    5. LlamaIndex
    6. AutoGPT
    7. BabyAGI
    8. Google's Minerva
    9. DeepMind's AlphaCode

    AI recommended 9 alternatives but never named openreasoner/openr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source frameworks exist for integrating advanced reasoning into LLM applications?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack (deepset/Haystack)
    4. DSPy
    5. AutoGPT
    6. PromptFlow

    AI recommended 6 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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openreasoner/openr — 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