RRepoGEO

REPOGEO REPORT · LITE

huangwl18/ReKep

Default branch main · commit 63c43fdb · scanned 6/12/2026, 4:32:53 AM

GitHub: 951 stars · 98 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 huangwl18/ReKep, 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 specific topics to improve categorization

    Why:

    COPY-PASTE FIX
    ["robotics", "manipulation", "keypoint-constraints", "spatio-temporal-reasoning", "large-vision-models", "vision-language-models", "robot-learning", "omnigibson"]
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    (Create a LICENSE file in the repository root with your chosen open-source license, e.g., MIT, Apache-2.0, or GPL-3.0.)
  • mediumreadme#3
    Reinforce the project's core purpose in the README's opening

    Why:

    CURRENT
    This is the official demo code for ReKep implemented in OmniGibson. ReKep is a method that uses large vision models and vision-language models in a hierarchical optimization framework to generate closed-loop trajectories for manipulation tasks.
    COPY-PASTE FIX
    This repository provides the official demo code for ReKep, a novel method implemented in OmniGibson that leverages large vision models and vision-language models within a hierarchical optimization framework to generate closed-loop trajectories for complex robotic manipulation tasks.

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 huangwl18/ReKep
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RT-X
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. RT-X · recommended 1×
  2. OpenVLA · recommended 1×
  3. Diffusion Policy · recommended 1×
  4. ViT · recommended 1×
  5. CLIP · recommended 1×
  • CATEGORY QUERY
    How to use large vision models for complex robotic manipulation trajectory generation?
    you: not recommended
    AI recommended (in order):
    1. RT-X
    2. OpenVLA
    3. Diffusion Policy
    4. ViT
    5. CLIP
    6. Perceiver IO
    7. ResNet
    8. RoboCat

    AI recommended 8 alternatives but never named huangwl18/ReKep. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks enable spatio-temporal reasoning with keypoint constraints for robot tasks?
    you: not recommended
    AI recommended (in order):
    1. GTSAM
    2. Open Motion Planning Library (OMPL)
    3. Drake
    4. PyBullet
    5. ROS (Robot Operating System) with MoveIt!
    6. Robotics Toolbox for MATLAB

    AI recommended 6 alternatives but never named huangwl18/ReKep. 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 huangwl18/ReKep?
    pass
    AI named huangwl18/ReKep explicitly

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

  • If a team adopts huangwl18/ReKep in production, what risks or prerequisites should they evaluate first?
    pass
    AI named huangwl18/ReKep 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 huangwl18/ReKep solve, and who is the primary audience?
    pass
    AI named huangwl18/ReKep explicitly

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

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huangwl18/ReKep — 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