RRepoGEO

REPOGEO REPORT · LITE

jim-schwoebel/awesome_ai_agents

Default branch main · commit 51b1a7eb · scanned 5/11/2026, 8:36:58 PM

GitHub: 1,742 stars · 502 forks

AI VISIBILITY SCORE
33 /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
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 jim-schwoebel/awesome_ai_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 README opening to clarify repo type and differentiate from frameworks

    Why:

    CURRENT
    Welcome to the **Ultimate Hub for AI Agents**, your one-stop destination for all things related to AI-driven agents.
    COPY-PASTE FIX
    Welcome to the **Ultimate Hub for AI Agents**, your definitive curated directory for all things related to AI-driven agents. This repository is a comprehensive, actively maintained list of tools, frameworks, datasets, and projects, *not* a framework or library itself.
  • mediumtopics#2
    Refine topics to emphasize 'list/directory' and remove 'framework' ambiguity

    Why:

    CURRENT
    agent-based-modeling, agentic, agentic-ai, agentic-workflow, agents, ai, ai-agent, ai-agent-framework, ai-agent-tools, ai-agents-cli, ai-agents-framework, aiagent, aiagents, aiworkflow, awesome-list, awesome-lists, learning, multi-agent, multi-agent-system, multi-agent-systems
    COPY-PASTE FIX
    agent-based-modeling, agentic, agentic-ai, agentic-workflow, agents, ai, ai-agent, ai-agent-tools, ai-agents-cli, aiagent, aiagents, aiworkflow, awesome-list, awesome-lists, learning, multi-agent, multi-agent-system, multi-agent-systems, ai-agent-resources, curated-collection, resource-directory
  • lowcomparison#3
    Add a 'Why this list?' section to explicitly contrast with frameworks

    Why:

    COPY-PASTE FIX
    ### Why Choose This Hub?
    
    Unlike AI agent frameworks such as LangChain or LlamaIndex, this repository does not provide a coding library. Instead, it serves as a comprehensive, curated directory designed to help you discover, evaluate, and understand the vast ecosystem of AI agents, tools, and research.

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 jim-schwoebel/awesome_ai_agents
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 3×
  2. run-llama/llama_index · recommended 3×
  3. ai-collection/awesome-ai-agents · recommended 1×
  4. Hugging Face Hub · recommended 1×
  5. Papers With Code · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of tools and frameworks for building AI agents?
    you: not recommended
    AI recommended (in order):
    1. Awesome-AI-Agents (ai-collection/awesome-ai-agents)
    2. Hugging Face Hub
    3. LangChain (langchain-ai/langchain)
    4. LlamaIndex (run-llama/llama_index)
    5. Papers With Code
    6. LangChain (langchain-ai/langchain)
    7. LlamaIndex (run-llama/llama_index)
    8. AutoGen (microsoft/autogen)
    9. CrewAI (joaomdmoura/crewAI)
    10. Haystack (deepset-ai/haystack)
    11. Open Interpreter (KillianLucas/open-interpreter)
    12. AgentVerse (OpenBMB/AgentVerse)

    AI recommended 12 alternatives but never named jim-schwoebel/awesome_ai_agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best resources to explore different types of AI agent architectures and projects?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym/Farama Foundation Gymnasium (Farama-Foundation/Gymnasium)
    2. Stable Baselines3 (DLR-RM/stable-baselines3)
    3. Hugging Face Agents (Transformers Agents) (huggingface/transformers)
    4. LangChain (langchain-ai/langchain)
    5. LlamaIndex (run-llama/llama_index)
    6. DeepMind Research Papers and Blog Posts
    7. Reinforcement Learning: An Introduction by Sutton and Barto

    AI recommended 7 alternatives but never named jim-schwoebel/awesome_ai_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 jim-schwoebel/awesome_ai_agents?
    pass
    AI named jim-schwoebel/awesome_ai_agents explicitly

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

  • If a team adopts jim-schwoebel/awesome_ai_agents in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jim-schwoebel/awesome_ai_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 jim-schwoebel/awesome_ai_agents solve, and who is the primary audience?
    pass
    AI did not name jim-schwoebel/awesome_ai_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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