RRepoGEO

REPOGEO REPORT · LITE

datawhalechina/handy-multi-agent

Default branch main · commit 44b0e8ed · scanned 6/9/2026, 1:42:00 AM

GitHub: 765 stars · 76 forks

AI VISIBILITY SCORE
28 /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
2 / 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 datawhalechina/handy-multi-agent, 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
    Add a clear English positioning statement to the README's opening

    Why:

    CURRENT
    # Handy Multi-Agent 教程
    COPY-PASTE FIX
    # Handy Multi-Agent 教程

This repository provides a practical guide and tutorial for building multi-agent systems from scratch, based on the CAMEL framework and focusing on LLM-powered agents.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    multi-agent-systems, llm-agents, camel-framework, ai-tutorial, agent-society, large-language-models, rag, memory
  • highlicense#3
    Create a LICENSE file with the specified Creative Commons license

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a LICENSE file in the root of the repository containing the full text of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), as indicated in the README badge.

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 datawhalechina/handy-multi-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Mesa
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Mesa · recommended 1×
  2. NetLogo · recommended 1×
  3. SPADE · recommended 1×
  4. JADE · recommended 1×
  5. Anylogic · recommended 1×
  • CATEGORY QUERY
    How can I learn to build multi-agent systems from the ground up?
    you: not recommended
    AI recommended (in order):
    1. Mesa
    2. NetLogo
    3. SPADE
    4. JADE
    5. Anylogic
    6. GAMA

    AI recommended 6 alternatives but never named datawhalechina/handy-multi-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a practical guide to implement LLM-based agent societies and understand their architecture.
    you: not recommended
    AI recommended (in order):
    1. AutoGen (microsoft/autogen)
    2. CrewAI (joaomdmoura/crewai)
    3. LangChain (langchain-ai/langchain)
    4. LlamaIndex (run-llama/llama_index)
    5. MetaGPT (Datawhale/MetaGPT)
    6. AgentVerse (OpenBMB/AgentVerse)

    AI recommended 6 alternatives but never named datawhalechina/handy-multi-agent. 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 datawhalechina/handy-multi-agent?
    pass
    AI did not name datawhalechina/handy-multi-agent — 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 datawhalechina/handy-multi-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named datawhalechina/handy-multi-agent 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 datawhalechina/handy-multi-agent solve, and who is the primary audience?
    pass
    AI named datawhalechina/handy-multi-agent explicitly

    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 datawhalechina/handy-multi-agent. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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datawhalechina/handy-multi-agent — 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