RRepoGEO

REPOGEO REPORT · LITE

OpenDriveLab/DriveAGI

Default branch main · commit 02a3ff07 · scanned 6/6/2026, 3:02:53 PM

GitHub: 800 stars · 34 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 OpenDriveLab/DriveAGI, 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's opening to clearly state its identity

    Why:

    CURRENT
    > [!IMPORTANT]
> 🌟 Stay up to date at opendrivelab.com!

## Table of Contents
    COPY-PASTE FIX
    > [!IMPORTANT]
> 🌟 Stay up to date at opendrivelab.com!

OpenDriveLab/DriveAGI is an open-ended, LLM-powered research framework for building generalist, end-to-end driver agents in autonomous driving. It integrates advanced models like GenAD (generalized predictive model) and Vista (driving world model) to tackle complex driving scenarios.

## Table of Contents
  • mediumtopics#2
    Add more specific topics to differentiate from generic ML

    Why:

    CURRENT
    autonomous-driving, embodied-ai, foundation-model, general-artificial-intelligence, large-dataset, policy-learning, video-dataset, video-generation, world-models
    COPY-PASTE FIX
    autonomous-driving, embodied-ai, foundation-model, general-artificial-intelligence, large-dataset, policy-learning, video-dataset, video-generation, world-models, driving-agent-framework, end-to-end-driving, llm-for-driving
  • lowabout#3
    Expand the 'about' description to emphasize its framework nature

    Why:

    CURRENT
    [CVPR 2024 Highlight] GenAD: Generalized Predictive Model for Autonomous Driving
    COPY-PASTE FIX
    [CVPR 2024 Highlight] DriveAGI: An LLM-powered, end-to-end research framework for generalized predictive models and world models in autonomous driving.

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 OpenDriveLab/DriveAGI
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow · recommended 1×
  2. Keras API · recommended 1×
  3. PyTorch · recommended 1×
  4. NVIDIA DriveWorks · recommended 1×
  5. Drive AGX Platform · recommended 1×
  • CATEGORY QUERY
    How can I build a generalized predictive model for autonomous driving systems using large datasets?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow
    2. Keras API
    3. PyTorch
    4. NVIDIA DriveWorks
    5. Drive AGX Platform
    6. OpenCV
    7. ROS (Robot Operating System)
    8. Apache Spark
    9. MLlib
    10. Caffe
    11. Caffe2

    AI recommended 11 alternatives but never named OpenDriveLab/DriveAGI. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best world model frameworks for long-horizon future prediction in embodied AI?
    you: not recommended
    AI recommended (in order):
    1. DreamerV3
    2. PlaNet (Planning Network)
    3. IRL (Implicit Regularization Learning)
    4. SimPLe (Simulated Policy Learning)
    5. MuZero
    6. VideoGPT / Phenaki
    7. Latent Imagination with Autoregressive Transformers (LIAT)

    AI recommended 7 alternatives but never named OpenDriveLab/DriveAGI. 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 OpenDriveLab/DriveAGI?
    pass
    AI named OpenDriveLab/DriveAGI explicitly

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

  • If a team adopts OpenDriveLab/DriveAGI in production, what risks or prerequisites should they evaluate first?
    pass
    AI named OpenDriveLab/DriveAGI 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 OpenDriveLab/DriveAGI solve, and who is the primary audience?
    pass
    AI named OpenDriveLab/DriveAGI 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 OpenDriveLab/DriveAGI. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/OpenDriveLab/DriveAGI.svg)](https://repogeo.com/en/r/OpenDriveLab/DriveAGI)
HTML
<a href="https://repogeo.com/en/r/OpenDriveLab/DriveAGI"><img src="https://repogeo.com/badge/OpenDriveLab/DriveAGI.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

OpenDriveLab/DriveAGI — 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