RRepoGEO

REPOGEO REPORT · LITE

intellicia-public/parastore

Default branch main · commit 4c97958d · scanned 6/15/2026, 2:37:48 AM

GitHub: 616 stars · 13 forks

AI VISIBILITY SCORE
35 /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
3 / 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 intellicia-public/parastore, 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 H1 and opening sentence to clarify core purpose

    Why:

    CURRENT
    <h1>Parastore</h1>

Build, simulate, and optimize retail spaces with synthetic consumers.
    COPY-PASTE FIX
    <h1>Parastore: LLM-driven 3D Retail Simulation</h1>

Build, simulate, and optimize retail spaces with synthetic consumers using AI agents.
  • highhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/intellicia-public/parastore
  • mediumcomparison#3
    Add a 'Comparison to Alternatives' section to the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

Parastore differs from general-purpose 3D engines like Unity or Unreal Engine by focusing specifically on LLM-driven synthetic consumer simulations for retail. While those platforms offer powerful rendering and physics, Parastore provides out-of-the-box LLM integration, persona generation, and pathfinding tailored for retail environments, rather than requiring extensive custom development for agent behavior.

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 intellicia-public/parastore
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Unity
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Unity · recommended 2×
  2. Unreal Engine · recommended 2×
  3. Unity-Technologies/ml-agents · recommended 1×
  4. projectmesa/mesa · recommended 1×
  5. AnyLogic · recommended 1×
  • CATEGORY QUERY
    How to simulate consumer behavior in a virtual retail store using AI agents?
    you: not recommended
    AI recommended (in order):
    1. Unity
    2. ML-Agents Toolkit (Unity-Technologies/ml-agents)
    3. Unreal Engine
    4. Mesa (projectmesa/mesa)
    5. AnyLogic
    6. NetLogo (NetLogo/NetLogo)
    7. OpenAI Gym (openai/gym)
    8. Stable Baselines3 (DLR-RM/stable-baselines3)
    9. Ray RLlib (ray-project/ray)

    AI recommended 9 alternatives but never named intellicia-public/parastore. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Open-source tool for building 3D retail simulations with LLM-driven synthetic shoppers?
    you: not recommended
    AI recommended (in order):
    1. Unity
    2. Unity ML-Agents Toolkit
    3. OpenAI GPT API
    4. Unreal Engine
    5. Unreal Engine Python API
    6. Godot Engine
    7. Blender
    8. Blender Python API
    9. Panda3D

    AI recommended 9 alternatives but never named intellicia-public/parastore. 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 intellicia-public/parastore?
    pass
    AI named intellicia-public/parastore explicitly

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

  • If a team adopts intellicia-public/parastore in production, what risks or prerequisites should they evaluate first?
    pass
    AI named intellicia-public/parastore 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 intellicia-public/parastore solve, and who is the primary audience?
    pass
    AI named intellicia-public/parastore explicitly

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

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intellicia-public/parastore — 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