RRepoGEO

REPOGEO REPORT · LITE

AGI-Edgerunners/LLM-Agents-Papers

Default branch main · commit aa40b127 · scanned 5/20/2026, 1:57:32 AM

GitHub: 2,299 stars · 147 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)

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

AI VISIBILITY SCORE
22 /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
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 AGI-Edgerunners/LLM-Agents-Papers, 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
  • highlicense#1
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) to clarify usage terms.
  • highreadme#2
    Reposition the README's opening to emphasize its curated nature and scope

    Why:

    CURRENT
    A repo lists papers related to LLM based agent.
    COPY-PASTE FIX
    A meticulously curated and actively updated repository listing research papers related to LLM-based agents, categorized by survey, technique, interaction, application, and more. This resource is designed for researchers, developers, and students seeking a structured overview of advancements in the LLM agent field.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Set the homepage URL in the repository's About section to `https://github.com/AGI-Edgerunners/LLM-Agents-Papers`.

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 AGI-Edgerunners/LLM-Agents-Papers
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. Hugging Face Blog · recommended 1×
  4. Hugging Face Papers · recommended 1×
  5. Semantic Scholar · recommended 1×
  • CATEGORY QUERY
    Where can I find recent research papers and comprehensive surveys on large language model agents?
    you: not recommended
    AI recommended (in order):
    1. arXiv.org
    2. Google Scholar
    3. Hugging Face Blog
    4. Hugging Face Papers
    5. Semantic Scholar
    6. Distill.pub
    7. OpenAI
    8. Google AI
    9. Anthropic
    10. DeepMind
    11. Alignment Research Center
    12. LessWrong
    13. AI Alignment Forum
    14. NeurIPS
    15. ICML
    16. ICLR
    17. ACL
    18. EMNLP
    19. AAAI
    20. IJCAI
    21. GitHub Repositories

    AI recommended 21 alternatives but never named AGI-Edgerunners/LLM-Agents-Papers. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for academic papers exploring advanced techniques for improving LLM agent performance and memory mechanisms.
    you: not recommended
    AI recommended (in order):
    1. Generative Agents: Interactive Simulacra of Human Behavior
    2. Recurrent Memory Transformer
    3. Self-Refine: Iterative Refinement with Self-Feedback
    4. Tree of Thoughts: Deliberate Problem Solving with Large Language Models
    5. ReAct: Synergizing Reasoning and Acting in Language Models
    6. Voyager: An Open-Ended Embodied Agent with Large Language Models
    7. Memory-Augmented Large Language Models are Computationally Universal

    AI recommended 7 alternatives but never named AGI-Edgerunners/LLM-Agents-Papers. 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 AGI-Edgerunners/LLM-Agents-Papers?
    pass
    AI did not name AGI-Edgerunners/LLM-Agents-Papers — 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 AGI-Edgerunners/LLM-Agents-Papers in production, what risks or prerequisites should they evaluate first?
    pass
    AI named AGI-Edgerunners/LLM-Agents-Papers 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 AGI-Edgerunners/LLM-Agents-Papers solve, and who is the primary audience?
    pass
    AI did not name AGI-Edgerunners/LLM-Agents-Papers — 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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AGI-Edgerunners/LLM-Agents-Papers — 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