RRepoGEO

REPOGEO REPORT · LITE

datawhalechina/hugging-multi-agent

Default branch main · commit 9ccd34a8 · scanned 6/27/2026, 1:37:51 PM

GitHub: 1,399 stars · 162 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

3 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 datawhalechina/hugging-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 concise English project summary immediately after the H1

    Why:

    COPY-PASTE FIX
    Add the following text directly after `# Hugging Multi-Agent`:

```
This repository provides a practical guide and tutorial for developers to understand and implement multi-agent systems, primarily based on the MetaGPT framework (ICLR 2024 Oral). It offers a comprehensive learning path from foundational concepts to practical development of complex multi-agent applications.
```
  • hightopics#2
    Add relevant topics for categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    multi-agent-systems, ai-agents, metagpt, tutorial, python, generative-ai, large-language-models
  • mediumlicense#3
    Add a standard open-source license file

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a `LICENSE` file in the repository root with the text of the Apache-2.0 License.

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/hugging-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 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Mesa · recommended 2×
  2. Artificial Intelligence: A Modern Approach · recommended 1×
  3. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence · recommended 1×
  4. Python · recommended 1×
  5. NumPy · recommended 1×
  • CATEGORY QUERY
    How can I learn to build and implement multi-agent AI systems from scratch?
    you: not recommended
    AI recommended (in order):
    1. Artificial Intelligence: A Modern Approach
    2. Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
    3. Python
    4. NumPy
    5. SciPy
    6. Matplotlib/Seaborn
    7. Pygame
    8. PettingZoo
    9. RLlib
    10. OpenSpiel
    11. Mesa
    12. NetLogo

    AI recommended 12 alternatives but never named datawhalechina/hugging-multi-agent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best frameworks for developing complex AI multi-agent applications with Python?
    you: not recommended
    AI recommended (in order):
    1. Mesa
    2. PetriNet
    3. SPADE
    4. Gymnasium
    5. Ray RLib
    6. Pyro
    7. SimPy

    AI recommended 7 alternatives but never named datawhalechina/hugging-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/hugging-multi-agent?
    pass
    AI named datawhalechina/hugging-multi-agent explicitly

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

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

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

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datawhalechina/hugging-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