RRepoGEO

REPOGEO REPORT · LITE

neural-maze/philoagents-course

Default branch main · commit b88d7731 · scanned 5/26/2026, 10:03:19 PM

GitHub: 1,496 stars · 321 forks

AI VISIBILITY SCORE
28 /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
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 neural-maze/philoagents-course, 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
  • highabout#1
    Clarify the repository description to emphasize 'course' and 'AI agents'

    Why:

    CURRENT
    When Philosophy meets AI
    COPY-PASTE FIX
    An open-source course to build AI agent simulations of philosophers using LLMs, LangGraph, and MongoDB.
  • highreadme#2
    Refine the README's main tagline to highlight 'course' and 'philosophical AI agents'

    Why:

    CURRENT
    Learn how to build an AI-powered game simulation engine to impersonate popular philosophers.
    COPY-PASTE FIX
    An open-source course: Learn to build AI agent simulations of historical philosophers for interactive learning and game environments.
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://theneuralmaze.substack.com/

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 neural-maze/philoagents-course
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Unity
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Unity · recommended 1×
  2. Unity-Technologies/ml-agents · recommended 1×
  3. Unreal Engine · recommended 1×
  4. AI Framework · recommended 1×
  5. godotengine/godot · recommended 1×
  • CATEGORY QUERY
    How to build an AI-powered simulation engine for interactive character interactions?
    you: not recommended
    AI recommended (in order):
    1. Unity
    2. ML-Agents Toolkit (Unity-Technologies/ml-agents)
    3. Unreal Engine
    4. AI Framework
    5. Godot Engine (godotengine/godot)
    6. Python
    7. Pygame (pygame/pygame)
    8. Panda3D (panda3d/panda3d)
    9. TensorFlow (tensorflow/tensorflow)
    10. Keras (keras-team/keras)
    11. PyTorch (pytorch/pytorch)
    12. Gymnasium (Farama-Foundation/Gymnasium)
    13. OpenAI Gym (openai/gym)
    14. Hugging Face Transformers (huggingface/transformers)
    15. GPT-2
    16. GPT-3.5
    17. Llama 2
    18. DeepMind Lab (deepmind/lab)
    19. DeepMind OpenSpiel (deepmind/open_spiel)

    AI recommended 19 alternatives but never named neural-maze/philoagents-course. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Tools for creating AI agents that simulate historical figures for educational or game purposes?
    you: not recommended
    AI recommended (in order):
    1. Inworld AI
    2. Character AI
    3. OpenAI GPT
    4. Anthropic Claude
    5. LangChain
    6. LlamaIndex
    7. DeepMotion

    AI recommended 7 alternatives but never named neural-maze/philoagents-course. 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 neural-maze/philoagents-course?
    pass
    AI named neural-maze/philoagents-course explicitly

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

  • If a team adopts neural-maze/philoagents-course in production, what risks or prerequisites should they evaluate first?
    pass
    AI named neural-maze/philoagents-course 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 neural-maze/philoagents-course solve, and who is the primary audience?
    pass
    AI did not name neural-maze/philoagents-course — 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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