RRepoGEO

REPOGEO REPORT · LITE

zhentingqi/rStar

Default branch main · commit cab41df6 · scanned 5/30/2026, 10:13:16 AM

GitHub: 970 stars · 110 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 zhentingqi/rStar, 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
    Add a concise 'About' description for the repository

    Why:

    COPY-PASTE FIX
    rStar is a self-play mutual reasoning approach that significantly improves the problem-solving capabilities of small language models (SLMs) without fine-tuning.
  • mediumreadme#2
    Add a problem-solution statement to the README's opening

    Why:

    CURRENT
    This repository contains necessary scripts to run **rStar**'s generator and discriminator.
    COPY-PASTE FIX
    This repository provides the implementation for **rStar**, a novel approach to enhance the reasoning and problem-solving abilities of small language models (SLMs) through self-play and mutual verification. It contains necessary scripts to run rStar's generator and discriminator.

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 zhentingqi/rStar
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 4 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 4×
  2. LlamaIndex · recommended 2×
  3. OpenAI's Function Calling · recommended 1×
  4. LangChain's Agents · recommended 1×
  5. Hugging Face's Transformers Agents · recommended 1×
  • CATEGORY QUERY
    How can I enhance reasoning in small language models without extensive fine-tuning?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. OpenAI's Function Calling
    4. LangChain's Agents
    5. Hugging Face's Transformers Agents

    AI recommended 5 alternatives but never named zhentingqi/rStar. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What methods improve language model problem-solving through self-play and mutual verification?
    you: not recommended
    AI recommended (in order):
    1. Auto-GPT
    2. LangChain
    3. GPT-4
    4. Claude
    5. LangChain
    6. LlamaIndex
    7. AutoGen
    8. CrewAI
    9. LangChain

    AI recommended 9 alternatives but never named zhentingqi/rStar. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 zhentingqi/rStar?
    pass
    AI named zhentingqi/rStar explicitly

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

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

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

Embed your GEO score

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MARKDOWN (README)
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zhentingqi/rStar — 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