RRepoGEO

REPOGEO REPORT · LITE

BAAI-Agents/Cradle

Default branch main · commit d7752fcc · scanned 5/12/2026, 5:22:54 AM

GitHub: 2,509 stars · 267 forks

AI VISIBILITY SCORE
40 /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
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 BAAI-Agents/Cradle, 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 the README H1 to specify 'Agent Framework' and 'Visual Input'

    Why:

    CURRENT
    # Cradle: Empowering Foundation Agents Towards General Computer Control
    COPY-PASTE FIX
    # Cradle: A Foundation Agent Framework for General Computer Control via Visual Input
  • mediumabout#2
    Integrate 'visual input' and 'human-like interaction' into the repository description

    Why:

    CURRENT
    The Cradle framework is a first attempt at General Computer Control (GCC). Cradle supports agents to ace any computer task by enabling strong reasoning abilities, self-improvment, and skill curation, in a standardized general environment with minimal requirements.
    COPY-PASTE FIX
    The Cradle framework is a first attempt at General Computer Control (GCC), enabling AI agents to ace any computer task using visual input (screenshots) and human-like interaction (keyboard & mouse). It supports strong reasoning, self-improvement, and skill curation in a standardized general environment with minimal requirements.
  • mediumreadme#3
    Add a 'Comparison' section to the README

    Why:

    COPY-PASTE FIX
    ## 💡 Comparison with Other Frameworks

Unlike general AI agent frameworks (e.g., LangChain, AutoGPT) that focus on orchestration or conversational patterns, Cradle is specifically designed as a comprehensive framework for **General Computer Control (GCC)**. While tools like PyAutoGUI or OpenCV offer low-level automation or computer vision capabilities, Cradle provides a high-level, standardized environment for foundation agents to perform complex computer tasks using the same unified interface humans use: **screenshots as input and keyboard & mouse operations as output**. This unique approach enables strong reasoning, self-improvement, and skill curation for agents interacting with any software or game.

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 BAAI-Agents/Cradle
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
opencv/opencv
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. opencv/opencv · recommended 2×
  2. pytorch/pytorch · recommended 2×
  3. tensorflow/tensorflow · recommended 2×
  4. openai/gym · recommended 1×
  5. Farama-Foundation/Gymnasium · recommended 1×
  • CATEGORY QUERY
    How to build AI agents that can control a computer using visual input?
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym (openai/gym)
    2. Farama Foundation Gymnasium (Farama-Foundation/Gymnasium)
    3. OpenCV (opencv/opencv)
    4. PyAutoGUI (asweigart/pyautogui)
    5. Microsoft Playwright (microsoft/playwright)
    6. PyTorch (pytorch/pytorch)
    7. TensorFlow (tensorflow/tensorflow)
    8. UiPath Studio
    9. Automation Anywhere
    10. Appium (appium/appium)
    11. OpenCV (opencv/opencv)
    12. PyTorch (pytorch/pytorch)
    13. TensorFlow (tensorflow/tensorflow)
    14. AutoHotkey (AutoHotkey/AutoHotkey)
    15. Python
    16. comtypes (enthought/comtypes)

    AI recommended 16 alternatives but never named BAAI-Agents/Cradle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Framework for developing AI agents capable of general computer task automation and self-improvement?
    you: not recommended
    AI recommended (in order):
    1. AutoGPT (Significant-Gravitas/AutoGPT)
    2. BabyAGI (yoheinakajima/babyagi)
    3. LangChain (langchain-ai/langchain)
    4. LlamaIndex (run-llama/llama_index)
    5. CrewAI (joaomdmoura/crewAI)
    6. Open Interpreter (KillianLucas/open-interpreter)
    7. Microsoft AutoGen (microsoft/autogen)

    AI recommended 7 alternatives but never named BAAI-Agents/Cradle. 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 BAAI-Agents/Cradle?
    pass
    AI named BAAI-Agents/Cradle explicitly

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

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

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

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BAAI-Agents/Cradle — 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