RRepoGEO

REPOGEO REPORT · LITE

ykhli/AI-tamago

Default branch main · commit a98a7352 · scanned 6/2/2026, 7:18:13 AM

GitHub: 520 stars · 82 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 ykhli/AI-tamago, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-pet, virtual-pet, tamagotchi, llm-application, javascript, nextjs, ollama, langchainjs, supabase
  • highreadme#2
    Clarify the README's opening sentence to emphasize 'application' nature

    Why:

    CURRENT
    A 100% local, LLM-generated and driven virtual pet with thoughts, feelings and feedback. Revive your fond memories of Tamagotchi! https://ai-tamago.fly.dev/
    COPY-PASTE FIX
    AI Tamago is a 100% local, LLM-generated and driven virtual pet with thoughts, feelings and feedback. This project serves as a complete, runnable example of an interactive AI companion application, demonstrating how to integrate various LLM and web technologies to revive your fond memories of Tamagotchi! https://ai-tamago.fly.dev/
  • mediumreadme#3
    Add a 'Key Features' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Key Features' (or similar) that lists core functionalities such as: 'LLM-driven thoughts and feelings', 'Persistent memory for pet interactions', 'Local-first operation with Ollama support', and 'Tamagotchi-style virtual pet simulation'.

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 ykhli/AI-tamago
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 1 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 1×
  2. ggerganov/llama.cpp · recommended 1×
  3. chroma-core/chroma · recommended 1×
  4. facebookresearch/faiss · recommended 1×
  5. deepset-ai/haystack · recommended 1×
  • CATEGORY QUERY
    How to build an interactive AI companion with persistent memory locally?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Llama.cpp (ggerganov/llama.cpp)
    3. ChromaDB (chroma-core/chroma)
    4. FAISS (facebookresearch/faiss)
    5. Haystack (deepset-ai/haystack)
    6. Weaviate (weaviate/weaviate)
    7. Hugging Face Transformers (huggingface/transformers)
    8. SQLite
    9. pickle
    10. Open Interpreter (KillianLucas/open-interpreter)
    11. GPT4All (nomic-ai/gpt4all)

    AI recommended 11 alternatives but never named ykhli/AI-tamago. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a JavaScript framework to create AI-powered interactive characters for web apps.
    you: not recommended
    AI recommended (in order):
    1. React
    2. TensorFlow.js
    3. Vue.js
    4. Three.js
    5. React Three Fiber
    6. Babylon.js
    7. PixiJS
    8. Next.js

    AI recommended 8 alternatives but never named ykhli/AI-tamago. 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 ykhli/AI-tamago?
    pass
    AI named ykhli/AI-tamago explicitly

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

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

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

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