RRepoGEO

REPOGEO REPORT · LITE

real-stanford/diffusion_policy

Default branch main · commit 5ba07ac6 · scanned 5/13/2026, 4:57:48 PM

GitHub: 4,129 stars · 771 forks

AI VISIBILITY SCORE
33 /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
2 / 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 real-stanford/diffusion_policy, 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 README H1 to clearly state the project's unique focus

    Why:

    CURRENT
    # Diffusion Policy
    COPY-PASTE FIX
    # Diffusion Policy: Visuomotor Policy Learning via Action Diffusion for Robotics
  • hightopics#2
    Add more specific topics to improve categorization

    Why:

    CURRENT
    robotics
    COPY-PASTE FIX
    robotics, diffusion-models, policy-learning, visuomotor-control, imitation-learning, deep-learning
  • mediumreadme#3
    Add a concise problem statement and differentiator to the README intro

    Why:

    COPY-PASTE FIX
    Diffusion Policy introduces a novel paradigm for visuomotor policy learning by applying diffusion models to generate robot actions. This approach offers a powerful alternative to traditional methods, enabling more robust and generalizable control policies for complex robotic 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 real-stanford/diffusion_policy
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RLlib
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. RLlib · recommended 2×
  2. Stable Baselines3 · recommended 1×
  3. OpenSpiel · recommended 1×
  4. Acme · recommended 1×
  5. Tianshou · recommended 1×
  • CATEGORY QUERY
    What frameworks are available for learning visuomotor policies for robotic control tasks?
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. Stable Baselines3
    3. OpenSpiel
    4. Acme
    5. Tianshou
    6. Surreal

    AI recommended 6 alternatives but never named real-stanford/diffusion_policy. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking tools to implement diffusion models for robot action generation and policy learning.
    you: not recommended
    AI recommended (in order):
    1. Diffusers
    2. PyTorch
    3. TensorFlow
    4. Keras
    5. OpenAI Gym
    6. Gymnasium
    7. RLlib
    8. ROS

    AI recommended 8 alternatives but never named real-stanford/diffusion_policy. 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 real-stanford/diffusion_policy?
    pass
    AI named real-stanford/diffusion_policy explicitly

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

  • If a team adopts real-stanford/diffusion_policy in production, what risks or prerequisites should they evaluate first?
    pass
    AI named real-stanford/diffusion_policy 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 real-stanford/diffusion_policy solve, and who is the primary audience?
    pass
    AI did not name real-stanford/diffusion_policy — likely talking about a different project

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

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real-stanford/diffusion_policy — 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