RRepoGEO

REPOGEO REPORT · LITE

zjunlp/LLMAgentPapers

Default branch main · commit 3855f982 · scanned 5/27/2026, 9:13:18 PM

GitHub: 3,019 stars · 182 forks

AI VISIBILITY SCORE
28 /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
2 / 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 zjunlp/LLMAgentPapers, 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
  • highabout#1
    Update 'About' description to clarify repo's nature

    Why:

    CURRENT
    Must-read Papers on LLM Agents.
    COPY-PASTE FIX
    A curated, must-read collection of research papers on Large Language Model Agents and multi-agent systems.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with your chosen open-source license (e.g., MIT, Apache-2.0, GPL-3.0).
  • mediumreadme#3
    Enhance README's opening statement to emphasize 'curated collection'

    Why:

    CURRENT
    Must-read Papers on Large Language Model Agents.
    COPY-PASTE FIX
    This repository presents a **curated, must-read collection of research papers** on Large Language Model Agents and multi-agent systems. Dive into the essential literature covering personality, memory, planning, tool use, and multi-agent communication.

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 zjunlp/LLMAgentPapers
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
arXiv.org
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. arXiv.org · recommended 1×
  2. Google Scholar · recommended 1×
  3. Papers With Code · recommended 1×
  4. Hugging Face Papers · recommended 1×
  5. Microsoft Academic · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive collection of research papers on large language model agents?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. Papers With Code
    4. Hugging Face Papers
    5. Microsoft Academic
    6. Semantic Scholar

    AI recommended 6 alternatives but never named zjunlp/LLMAgentPapers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the essential research papers for understanding multi-agent systems powered by large language models?
    you: not recommended
    AI recommended (in order):
    1. CAMEL
    2. AutoGPT
    3. Voyager
    4. MetaGPT

    AI recommended 4 alternatives but never named zjunlp/LLMAgentPapers. 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 zjunlp/LLMAgentPapers?
    pass
    AI named zjunlp/LLMAgentPapers explicitly

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

  • If a team adopts zjunlp/LLMAgentPapers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named zjunlp/LLMAgentPapers 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 zjunlp/LLMAgentPapers solve, and who is the primary audience?
    pass
    AI did not name zjunlp/LLMAgentPapers — 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?

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zjunlp/LLMAgentPapers — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite