RRepoGEO

REPOGEO REPORT · LITE

EvoAgentX/Awesome-Self-Evolving-Agents

Default branch main · commit ab0c0118 · scanned 6/26/2026, 2:43:00 AM

GitHub: 2,273 stars · 171 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 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 it's a survey/awesome list

    Why:

    CURRENT
    The current README starts with a generic "Awesome-Self-Evolving-Agents" title and "We're still cooking" message.
    COPY-PASTE FIX
    Add this sentence immediately after the main title: "This repository serves as a comprehensive survey and curated awesome list of resources for self-evolving AI agents, bridging foundation models and lifelong agentic systems."
  • mediumtopics#2
    Add 'awesome-list' and 'survey' 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, awesome-list, survey
  • lowreadme#3
    Prominently link to the associated survey paper in the README

    Why:

    CURRENT
    [](https://arxiv.org/abs/2508.07407) (a broken link in the header)
    COPY-PASTE FIX
    Replace the broken link with: "Read the full survey paper on arXiv: [A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems](https://arxiv.org/abs/2508.07407)" and place it prominently near the top of the README.

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
Ray RLlib
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ray RLlib · recommended 1×
  2. OpenAI Gym / Farama Foundation Gymnasium · recommended 1×
  3. Stable Baselines3 (SB3) · recommended 1×
  4. TensorFlow Agents (TF-Agents) · recommended 1×
  5. PyTorch Lightning · recommended 1×
  • CATEGORY QUERY
    How to build AI agents that can adapt and improve over time?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. OpenAI Gym / Farama Foundation Gymnasium
    3. Stable Baselines3 (SB3)
    4. TensorFlow Agents (TF-Agents)
    5. PyTorch Lightning
    6. DEAP (Distributed Evolutionary Algorithms in Python)
    7. JAX

    AI recommended 7 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 dynamic multi-agent systems using large language models?
    you: not recommended
    AI recommended (in order):
    1. AutoGen
    2. CrewAI
    3. LangChain Agents
    4. LlamaIndex Agents
    5. MetaGPT
    6. AgentVerse

    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?

Embed your GEO score

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MARKDOWN (README)
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EvoAgentX/Awesome-Self-Evolving-Agents — 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