RRepoGEO

REPOGEO REPORT · LITE

weitianxin/Awesome-Agentic-Reasoning

Default branch main · commit 8e0fbffd · scanned 5/16/2026, 10:22:41 AM

GitHub: 1,240 stars · 95 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 weitianxin/Awesome-Agentic-Reasoning, 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
    Update README H1 to clarify its nature as a curated collection and survey companion

    Why:

    CURRENT
    # Awesome Agentic Reasoning Papers
    COPY-PASTE FIX
    # Awesome Agentic Reasoning Papers: A Curated Collection & Survey Companion
  • mediumreadme#2
    Add a 'Target Audience' section to the README

    Why:

    COPY-PASTE FIX
    ## 🎯 Target Audience
    This repository is primarily for researchers, students, and practitioners seeking a comprehensive academic overview and curated collection of papers on agentic reasoning for Large Language Models. It serves as a companion to the "Agentic Reasoning for Large Language Models: A Survey" paper, providing organized resources for in-depth study rather than direct implementation frameworks.
  • lowtopics#3
    Expand GitHub topics with more specific 'collection' keywords

    Why:

    CURRENT
    agent, agentic-ai, awesome-resources, generative-ai, large-language-models, reasoning, survey
    COPY-PASTE FIX
    agent, agentic-ai, awesome-resources, generative-ai, large-language-models, reasoning, survey, paper-collection, research-papers, literature-review

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 weitianxin/Awesome-Agentic-Reasoning
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tree of Thoughts
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Tree of Thoughts · recommended 1×
  2. Reflexion · recommended 1×
  3. AutoGPT · recommended 1×
  4. BabyAGI · recommended 1×
  5. OpenAI · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive overview of agentic reasoning research for large language models?
    you: not recommended
    AI recommended (in order):
    1. Tree of Thoughts
    2. Reflexion
    3. AutoGPT
    4. BabyAGI
    5. OpenAI
    6. Learn Prompting

    AI recommended 6 alternatives but never named weitianxin/Awesome-Agentic-Reasoning. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources for understanding agentic AI systems, including planning and tool use?
    you: not recommended
    AI recommended (in order):
    1. Generative Agents: Interactive Simulacra of Human Behavior (joonspk-research/generative_agents)
    2. LlamaIndex (LlamaIndex/LlamaIndex)
    3. LangChain (langchain-ai/langchain)
    4. Reflexion: An Autonomous Agent with Dynamic Memory and Self-Reflection (noahshinn024/reflexion)
    5. AutoGPT (Significant-Gravitas/AutoGPT)
    6. BabyAGI (yoheinakajima/babyagi)
    7. Toolformer: Language Models Can Teach Themselves to Use Tools (facebookresearch/toolformer)
    8. Voyager: An Open-Ended Embodied Agent with Large Language Models (MineDojo/Voyager)

    AI recommended 8 alternatives but never named weitianxin/Awesome-Agentic-Reasoning. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 weitianxin/Awesome-Agentic-Reasoning?
    pass
    AI named weitianxin/Awesome-Agentic-Reasoning explicitly

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

  • If a team adopts weitianxin/Awesome-Agentic-Reasoning in production, what risks or prerequisites should they evaluate first?
    pass
    AI named weitianxin/Awesome-Agentic-Reasoning 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 weitianxin/Awesome-Agentic-Reasoning solve, and who is the primary audience?
    pass
    AI named weitianxin/Awesome-Agentic-Reasoning 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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weitianxin/Awesome-Agentic-Reasoning — 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