RRepoGEO

REPOGEO REPORT · LITE

vectorize-io/self-driving-agents

Default branch main · commit 743da5c9 · scanned 6/25/2026, 7:07:01 PM

GitHub: 931 stars · 124 forks

AI VISIBILITY SCORE
17 /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
1 / 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 vectorize-io/self-driving-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

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

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A complete AI workforce in a box: 179 ready-to-use, self-learning AI agents organized into 13 departments, deployable via npx.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or GPL-3.0) in the repository root to clearly state the project's licensing terms.

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 vectorize-io/self-driving-agents
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LangServe · recommended 1×
  3. Microsoft Azure AI Studio · recommended 1×
  4. Azure OpenAI Service · recommended 1×
  5. Google Cloud Vertex AI Agent Builder · recommended 1×
  • CATEGORY QUERY
    How to easily deploy a collection of specialized AI agents for business tasks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LangServe
    3. Microsoft Azure AI Studio
    4. Azure OpenAI Service
    5. Google Cloud Vertex AI Agent Builder
    6. Hugging Face Inference Endpoints
    7. AWS Bedrock
    8. AWS Lambda
    9. AWS ECS
    10. AWS EKS
    11. OpenAI Assistants API
    12. Python
    13. FastAPI
    14. CrewAI
    15. AutoGen
    16. DigitalOcean
    17. Render
    18. Fly.io

    AI recommended 18 alternatives but never named vectorize-io/self-driving-agents. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a framework to manage and orchestrate multiple AI agents for diverse roles.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    3. Haystack (deepset-ai/haystack)
    4. AutoGPT (Significant-Gravitas/AutoGPT)
    5. CrewAI (joaomdmoura/crewai)
    6. LlamaIndex (run-llama/llama_index)

    AI recommended 6 alternatives but never named vectorize-io/self-driving-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
    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 vectorize-io/self-driving-agents?
    pass
    AI did not name vectorize-io/self-driving-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?

  • If a team adopts vectorize-io/self-driving-agents in production, what risks or prerequisites should they evaluate first?
    pass
    AI did not name vectorize-io/self-driving-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?

  • In one sentence, what problem does the repo vectorize-io/self-driving-agents solve, and who is the primary audience?
    pass
    AI named vectorize-io/self-driving-agents explicitly

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

Embed your GEO score

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MARKDOWN (README)
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vectorize-io/self-driving-agents — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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