RRepoGEO

REPOGEO REPORT · LITE

weitianxin/Awesome-Agentic-Reasoning

Default branch main · commit 8e0fbffd · scanned 6/27/2026, 6:38:23 AM

GitHub: 1,299 stars · 101 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
27 /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
1 / 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
    Reposition the README's opening paragraph to explicitly state it's an 'awesome curated list' based on a survey

    Why:

    CURRENT
    This repository organizes research by thematic areas that integrate reasoning with action, including planning, tool use, search, self-evolution through memory and feedback, multi-agent systems, and real-world applications and benchmarks.
    COPY-PASTE FIX
    This repository is an **awesome curated list of research papers and resources** on Agentic Reasoning for Large Language Models, based on our comprehensive survey. It organizes research by thematic areas that integrate reasoning with action, including planning, tool use, search, self-evolution through memory and feedback, multi-agent systems, and real-world applications and benchmarks.
  • mediumreadme#2
    Add a concise 'What is this repo?' section or expand the introduction

    Why:

    COPY-PASTE FIX
    Add a new section or expand the existing '🌟 Introduction' with: 'This repository serves as a living, curated collection of essential research papers and resources on Agentic Reasoning for Large Language Models. It is designed for researchers, developers, and enthusiasts seeking to understand and explore the latest advancements in LLM agent planning, tool use, self-evolution, and multi-agent systems, directly complementing our survey paper.'
  • lowtopics#3
    Expand repository topics with more specific 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, awesome-list, llm-agents, agent-planning, tool-use, self-evolution, multi-agent-systems

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
Awesome-LLM-Agents
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Awesome-LLM-Agents · recommended 1×
  2. Agent AI · recommended 1×
  3. A Survey on Large Language Model based Agents · recommended 1×
  4. The Rise and Potential of Large Language Model Based Agents: A Survey · recommended 1×
  5. Papers With Code · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of research papers on agentic reasoning for LLMs?
    you: not recommended
    AI recommended (in order):
    1. Awesome-LLM-Agents
    2. Agent AI
    3. A Survey on Large Language Model based Agents
    4. The Rise and Potential of Large Language Model Based Agents: A Survey
    5. Papers With Code
    6. AI Agent List

    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 leading research papers on LLM agent planning, tool use, and self-evolution?
    you: not recommended
    AI recommended (in order):
    1. ReAct
    2. Toolformer
    3. Voyager
    4. Generative Agents
    5. Reflexion
    6. AutoGPT
    7. Tree of Thoughts

    AI recommended 7 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 did not name weitianxin/Awesome-Agentic-Reasoning — likely talking about a different project

    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 did not name weitianxin/Awesome-Agentic-Reasoning — likely talking about a different project

    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