RRepoGEO

REPOGEO REPORT · LITE

pat-jj/Awesome-Adaptation-of-Agentic-AI

Default branch main · commit 8c37381e · scanned 6/13/2026, 8:27:41 PM

GitHub: 663 stars · 59 forks

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 pat-jj/Awesome-Adaptation-of-Agentic-AI, 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 to clearly state it's an 'Awesome List' of research papers

    Why:

    CURRENT
    A curated list of papers on adaptation strategies of agentic AI systems. This repository accompanies the paper "Adaptation of Agentic AI" (Ongoing Work).
    COPY-PASTE FIX
    This is an **Awesome List** of cutting-edge research papers focusing on adaptation strategies for agentic AI systems. It serves as a comprehensive, curated resource for researchers and practitioners exploring the evolving field of Agentic AI adaptation, accompanying our ongoing work, "Adaptation of Agentic AI".
  • hightopics#2
    Add 'awesome-list' and 'research-papers' to the repository topics

    Why:

    CURRENT
    adaptation, agentic-ai, large-language-models
    COPY-PASTE FIX
    adaptation, agentic-ai, large-language-models, awesome-list, research-papers
  • mediumlicense#3
    Add a clear statement about the repository's license to the README

    Why:

    COPY-PASTE FIX
    ## License
This repository is licensed under the terms specified in the [LICENSE](LICENSE) file. Please refer to the file for full details on usage and distribution.

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 pat-jj/Awesome-Adaptation-of-Agentic-AI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. OpenAI GPT-4/GPT-3.5 · recommended 1×
  4. Anthropic Claude 3 · recommended 1×
  5. Google Gemini 1.5 Pro · recommended 1×
  • CATEGORY QUERY
    What are effective strategies for large language model agents to adapt to new tasks?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4/GPT-3.5
    2. Anthropic Claude 3
    3. Google Gemini 1.5 Pro
    4. Hugging Face Transformers Library
    5. OpenAI Fine-tuning API
    6. Google Cloud Vertex AI
    7. MosaicML
    8. LangChain
    9. LlamaIndex
    10. Pinecone
    11. Weaviate
    12. OpenAI API
    13. Hugging Face TRL Library
    14. Argilla
    15. LangChain Agents
    16. Auto-GPT/BabyAGI
    17. OpenAI Function Calling
    18. Google Gemini

    AI recommended 18 alternatives but never named pat-jj/Awesome-Adaptation-of-Agentic-AI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking research on dynamic tool adaptation methods for autonomous AI agent systems.
    you: not recommended
    AI recommended (in order):
    1. Toolformer
    2. REACT
    3. AutoGPT
    4. BabyAGI
    5. LangChain
    6. LlamaIndex
    7. Voyager
    8. Gorilla
    9. ALF

    AI recommended 9 alternatives but never named pat-jj/Awesome-Adaptation-of-Agentic-AI. 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 pat-jj/Awesome-Adaptation-of-Agentic-AI?
    pass
    AI did not name pat-jj/Awesome-Adaptation-of-Agentic-AI — 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 pat-jj/Awesome-Adaptation-of-Agentic-AI in production, what risks or prerequisites should they evaluate first?
    pass
    AI named pat-jj/Awesome-Adaptation-of-Agentic-AI 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 pat-jj/Awesome-Adaptation-of-Agentic-AI solve, and who is the primary audience?
    pass
    AI did not name pat-jj/Awesome-Adaptation-of-Agentic-AI — 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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pat-jj/Awesome-Adaptation-of-Agentic-AI — 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