RRepoGEO

REPOGEO REPORT · LITE

OpenBMB/ProAgent

Default branch main · commit 02a79ac6 · scanned 6/3/2026, 3:53:15 AM

GitHub: 863 stars · 94 forks

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 OpenBMB/ProAgent, 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
  • highreadme#1
    Reposition the README's opening paragraph to be solution-oriented

    Why:

    CURRENT
    From water wheels to Robotic Process Automation (RPA), automation technology has evolved throughout history to liberate human beings from arduous tasks. Yet, RPA struggles with tasks needing human-like intelligence, especially in elaborate design of workflow construction and dynamic decision-making in workflow execution. As Large Language Models (LLMs) have emerged human-like intelligence, this paper introduces `Agentic Process Automation`(APA), a groundbreaking automation paradigm using LLM-based agents for advanced automation by offloading the human labor to agents associated with construction and execution. We then instantiate `ProAgent`, an LLM-based agent designed to craft workflows from human instructions and make intricate decisions by coordinating specialized agents.
    COPY-PASTE FIX
    **ProAgent is an LLM-based agent system designed for Agentic Process Automation (APA), enabling intelligent automation of complex business workflows beyond traditional RPA.** It empowers users to craft dynamic workflows from human instructions and make intricate decisions by coordinating specialized AI agents. ProAgent addresses the limitations of Robotic Process Automation (RPA) by leveraging Large Language Models (LLMs) to handle tasks requiring human-like intelligence in workflow construction and execution. This repository provides the official code for the `Agentic Process Automation` paradigm.
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://github.com/OpenBMB/ProAgent/blob/main/README.md (or a dedicated project page/paper link if available)

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 OpenBMB/ProAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
langchain-ai/langchain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. langchain-ai/langchain · recommended 2×
  2. run-llama/llama_index · recommended 2×
  3. huggingface/transformers · recommended 2×
  4. OpenAI GPT-4 / GPT-3.5 Turbo · recommended 1×
  5. Anthropic Claude · recommended 1×
  • CATEGORY QUERY
    How can I use large language models to automate complex business processes beyond traditional RPA?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT-4 / GPT-3.5 Turbo
    2. LangChain (langchain-ai/langchain)
    3. LlamaIndex (run-llama/llama_index)
    4. Anthropic Claude
    5. Hugging Face Transformers (huggingface/transformers)
    6. Llama 2
    7. Mistral
    8. Falcon
    9. Microsoft Azure OpenAI Service
    10. Google Cloud Vertex AI
    11. Zapier
    12. Make

    AI recommended 12 alternatives but never named OpenBMB/ProAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help build intelligent automation workflows that adapt dynamically using AI agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. Microsoft Semantic Kernel (microsoft/semantic-kernel)
    3. LlamaIndex (run-llama/llama_index)
    4. AutoGPT (Significant-Gravitas/AutoGPT)
    5. BabyAGI (yoheinakajima/babyagi)
    6. Zapier NLA
    7. Robocorp (robocorp/rpaframework)
    8. OpenAI API
    9. Anthropic API
    10. Hugging Face Transformers (huggingface/transformers)

    AI recommended 10 alternatives but never named OpenBMB/ProAgent. 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 OpenBMB/ProAgent?
    pass
    AI named OpenBMB/ProAgent explicitly

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

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

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

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MARKDOWN (README)
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OpenBMB/ProAgent — 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