RRepoGEO

REPOGEO REPORT · LITE

victordibia/designing-multiagent-systems

Default branch main · commit 1aebb311 · scanned 6/6/2026, 7:36:53 PM

GitHub: 584 stars · 152 forks

AI VISIBILITY SCORE
27 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 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 victordibia/designing-multiagent-systems, 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 opening to clarify educational purpose and distinguish from production frameworks

    Why:

    CURRENT
    Official code repository for Designing Multi-Agent Systems: Principles, Patterns, and Implementation for AI Agents by Victor Dibia. ... This repository includes **PicoAgents**—a full-featured multi-agent framework built entirely from scratch for the sole purpose of teaching you how multi-agent systems work.
    COPY-PASTE FIX
    This is the official companion code repository for the book 'Designing Multi-Agent Systems: Principles, Patterns, and Implementation for AI Agents' by Victor Dibia. It provides complete, tested implementations, including **PicoAgents**—an educational multi-agent framework built from scratch *for the sole purpose of teaching* core concepts, not as a production-ready library.
  • mediumabout#2
    Update repository description to emphasize its role as a book companion and learning resource

    Why:

    CURRENT
    Building LLM-Enabled Multi Agent Applications from Scratch
    COPY-PASTE FIX
    Companion code for 'Designing Multi-Agent Systems,' teaching principles and patterns for LLM-enabled multi-agent applications.
  • mediumtopics#3
    Add educational and book-related topics

    Why:

    CURRENT
    agents, autogen, generative-ai, large-language-models, multiagent-systems
    COPY-PASTE FIX
    agents, autogen, generative-ai, large-language-models, multiagent-systems, education, learning-resource, book-companion

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 victordibia/designing-multiagent-systems
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
hwchase17/langchain
Recommended in 3 of 2 queries
COMPETITOR LEADERBOARD
  1. hwchase17/langchain · recommended 3×
  2. microsoft/autogen · recommended 3×
  3. apache/kafka · recommended 3×
  4. LangChain · recommended 1×
  5. LlamaIndex · recommended 1×
  • CATEGORY QUERY
    Looking for resources to learn building multi-agent LLM applications from fundamental concepts.
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGen
    4. CrewAI
    5. OpenAI Function Calling
    6. Assistants API

    AI recommended 6 alternatives but never named victordibia/designing-multiagent-systems. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are effective design patterns for orchestrating multiple generative AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain (hwchase17/langchain)
    2. LlamaIndex (run-llama/llama_index)
    3. AutoGen (microsoft/autogen)
    4. LangChain (hwchase17/langchain)
    5. OpenAI Assistants API
    6. Prefect (PrefectHQ/prefect)
    7. Apache Airflow (apache/airflow)
    8. Redis (redis/redis)
    9. Apache Kafka (apache/kafka)
    10. PostgreSQL
    11. MongoDB
    12. AutoGen (microsoft/autogen)
    13. RabbitMQ (rabbitmq/rabbitmq-server)
    14. Apache Kafka (apache/kafka)
    15. LangChain (hwchase17/langchain)
    16. AutoGen (microsoft/autogen)
    17. BabyAGI (yoheinakajima/babyagi)
    18. Auto-GPT (Significant-Gravitas/Auto-GPT)
    19. Kafka (apache/kafka)

    AI recommended 19 alternatives but never named victordibia/designing-multiagent-systems. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 victordibia/designing-multiagent-systems?
    pass
    AI did not name victordibia/designing-multiagent-systems — 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 victordibia/designing-multiagent-systems in production, what risks or prerequisites should they evaluate first?
    pass
    AI named victordibia/designing-multiagent-systems 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 victordibia/designing-multiagent-systems solve, and who is the primary audience?
    pass
    AI did not name victordibia/designing-multiagent-systems — 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?

Embed your GEO score

Drop this badge into the README of victordibia/designing-multiagent-systems. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/victordibia/designing-multiagent-systems.svg)](https://repogeo.com/en/r/victordibia/designing-multiagent-systems)
HTML
<a href="https://repogeo.com/en/r/victordibia/designing-multiagent-systems"><img src="https://repogeo.com/badge/victordibia/designing-multiagent-systems.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

victordibia/designing-multiagent-systems — 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