RRepoGEO

REPOGEO REPORT · LITE

thunlp/ProactiveAgent

Default branch main · commit 3fcf9bee · scanned 6/4/2026, 10:17:49 PM

GitHub: 606 stars · 60 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 thunlp/ProactiveAgent, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    llm-agent, proactive-ai, large-language-models, agentic-ai, ai-assistant, task-automation, self-reflection
  • highreadme#2
    Strengthen the README's opening paragraph to emphasize proactive LLM agent capabilities

    Why:

    CURRENT
    This project (Proactive Agent) aims to construct a fully active agent, who may anticipate user's requirements and take the initiative, offering assistance and suggesting actions without explicit requests from user.
    COPY-PASTE FIX
    Proactive Agent is an advanced LLM-based framework designed to empower AI agents with the ability to anticipate user needs and proactively initiate helpful actions, moving beyond reactive responses. It provides a complete pipeline for data collection, generation, evaluation, and LLM fine-tuning to build truly autonomous and anticipatory AI assistants.
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2410.12361

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 thunlp/ProactiveAgent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Dialogflow ES/CX
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Dialogflow ES/CX · recommended 1×
  2. Rasa · recommended 1×
  3. Microsoft Azure LUIS · recommended 1×
  4. TensorFlow · recommended 1×
  5. Keras · recommended 1×
  • CATEGORY QUERY
    How to develop an AI agent that proactively anticipates user needs and suggests actions?
    you: not recommended
    AI recommended (in order):
    1. Google Dialogflow ES/CX
    2. Rasa
    3. Microsoft Azure LUIS
    4. TensorFlow
    5. Keras
    6. PyTorch
    7. scikit-learn
    8. Apache Mahout
    9. Surprise
    10. LightFM
    11. Redis
    12. PostgreSQL
    13. MongoDB
    14. Flask
    15. Django
    16. Express.js
    17. Apache Kafka

    AI recommended 17 alternatives but never named thunlp/ProactiveAgent. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable large language models to autonomously identify and initiate user tasks?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGPT
    4. Microsoft Semantic Kernel
    5. Haystack

    AI recommended 5 alternatives but never named thunlp/ProactiveAgent. 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 thunlp/ProactiveAgent?
    pass
    AI named thunlp/ProactiveAgent explicitly

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

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