RRepoGEO

REPOGEO REPORT · LITE

seanpixel/Teenage-AGI

Default branch main · commit e463e6e1 · scanned 6/12/2026, 1:23:08 AM

GitHub: 909 stars · 115 forks

AI VISIBILITY SCORE
30 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 seanpixel/Teenage-AGI, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise description to the repository's 'About' section

    Why:

    COPY-PASTE FIX
    A simplified, open-source implementation for an autonomous AI agent that can pursue a goal by managing and executing tasks, primarily for developers and AI enthusiasts exploring agentic AI.
  • mediumreadme#2
    Strengthen the README's opening sentence to clearly state it's an AI agent implementation

    Why:

    CURRENT
    Inspired by several Auto-GPT-related Projects (predominantly BabyAGI) and the Paper "Generative Agents: Interactive Simulacra of Human Behavior", this Python project uses OpenAI and Pinecone to Give memory to an AI agent and also allows it to "think" before making an action (outputting text).
    COPY-PASTE FIX
    Teenage-AGI is a Python project implementing an autonomous AI agent, inspired by BabyAGI and Generative Agents. It uses OpenAI and Pinecone to give the agent persistent memory and pre-action thinking capabilities.

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 seanpixel/Teenage-AGI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. Pinecone · recommended 2×
  4. Weaviate · recommended 2×
  5. Qdrant · recommended 2×
  • CATEGORY QUERY
    How to build an AI agent with persistent memory and pre-action thinking capabilities?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Pinecone
    4. Weaviate
    5. Qdrant
    6. OpenAI API
    7. Hugging Face Transformers
    8. Sentence-Transformers

    AI recommended 8 alternatives but never named seanpixel/Teenage-AGI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Python library to implement long-term memory and reasoning for autonomous agents.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack (deepset/Haystack)
    4. Faiss
    5. Pinecone
    6. Weaviate
    7. Qdrant
    8. Neo4j

    AI recommended 8 alternatives but never named seanpixel/Teenage-AGI. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    fail

    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 seanpixel/Teenage-AGI?
    pass
    AI named seanpixel/Teenage-AGI explicitly

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

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

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

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seanpixel/Teenage-AGI — 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