RRepoGEO

REPOGEO REPORT · LITE

EvoAgentX/Awesome-Self-Evolving-Agents

Default branch main · commit 7cb8abc6 · scanned 5/15/2026, 10:48:25 AM

GitHub: 2,141 stars · 152 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 EvoAgentX/Awesome-Self-Evolving-Agents, 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 clarify its nature as a survey/awesome list

    Why:

    CURRENT
    The README's immediate content after the H1 is 'We're still cooking — Stay tuned!'.
    COPY-PASTE FIX
    Insert the following text directly after the `<h1>` tag: `<p align="center">A comprehensive survey and curated awesome list of self-evolving AI agents, bridging foundation models and lifelong agentic systems.</p>`
  • mediumtopics#2
    Add 'survey' and 'awesome-list' to the repository topics

    Why:

    CURRENT
    agent, agentic-ai, ai, llms, multi-agent-systems, natural-language-processing, self-evolving
    COPY-PASTE FIX
    agent, agentic-ai, ai, llms, multi-agent-systems, natural-language-processing, self-evolving, survey, awesome-list
  • lowabout#3
    Update the repository description to explicitly include 'awesome list'

    Why:

    CURRENT
    [Survey] A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems
    COPY-PASTE FIX
    [Awesome List & Survey] A Comprehensive Survey and Curated List of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic 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 EvoAgentX/Awesome-Self-Evolving-Agents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. AutoGPT · recommended 1×
  5. OpenAI Assistants API · recommended 1×
  • CATEGORY QUERY
    How to build AI agents that can learn and adapt over time using large language models?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGPT
    5. OpenAI Assistants API

    AI recommended 5 alternatives but never named EvoAgentX/Awesome-Self-Evolving-Agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks for developing multi-agent systems with adaptive capabilities?
    you: not recommended
    AI recommended (in order):
    1. Mesa (projectmesa/mesa)
    2. SPADE (spade-foundation/spade)
    3. JADE
    4. NetLogo
    5. Anylogic
    6. GAMA (gama-platform/gama)

    AI recommended 6 alternatives but never named EvoAgentX/Awesome-Self-Evolving-Agents. 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 EvoAgentX/Awesome-Self-Evolving-Agents?
    pass
    AI did not name EvoAgentX/Awesome-Self-Evolving-Agents — 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 EvoAgentX/Awesome-Self-Evolving-Agents in production, what risks or prerequisites should they evaluate first?
    pass
    AI named EvoAgentX/Awesome-Self-Evolving-Agents 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 EvoAgentX/Awesome-Self-Evolving-Agents solve, and who is the primary audience?
    pass
    AI did not name EvoAgentX/Awesome-Self-Evolving-Agents — 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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EvoAgentX/Awesome-Self-Evolving-Agents — RepoGEO report