RRepoGEO

REPOGEO REPORT · LITE

reinforcement-learning-kr/lets-do-irl

Default branch master · commit 2ce7496d · scanned 6/3/2026, 5:27:59 AM

GitHub: 782 stars · 116 forks

AI VISIBILITY SCORE
28 /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
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 reinforcement-learning-kr/lets-do-irl, 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
    Emphasize the comparison aspect in the README introduction

    Why:

    CURRENT
    This repository contains PyTorch (v0.4.1) implementations of **Inverse Reinforcement Learning (IRL)** algorithms.
    COPY-PASTE FIX
    This repository contains PyTorch (v0.4.1) implementations of **Inverse Reinforcement Learning (IRL)** algorithms, designed for easy comparison and study of different approaches.
  • mediumtopics#2
    Add broader topics to signal 'implementations' and 'code'

    Why:

    CURRENT
    app, gail, inverse-reinforcement-learning, irl, maxent, pytorch, vail
    COPY-PASTE FIX
    app, gail, inverse-reinforcement-learning, irl, maxent, pytorch, vail, irl-implementations, reinforcement-learning-code
  • lowhomepage#3
    Add the repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/reinforcement-learning-kr/lets-do-irl

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 reinforcement-learning-kr/lets-do-irl
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
DLR-RM/stable-baselines3
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. DLR-RM/stable-baselines3 · recommended 1×
  2. Farama-Foundation/Gymnasium · recommended 1×
  3. HumanCompatibleAI/imitation · recommended 1×
  4. pytorch/rl · recommended 1×
  5. ray-project/ray · recommended 1×
  • CATEGORY QUERY
    How can I implement inverse reinforcement learning algorithms using a PyTorch framework?
    you: not recommended
    AI recommended (in order):
    1. Stable Baselines3 (DLR-RM/stable-baselines3)
    2. Gymnasium (Farama-Foundation/Gymnasium)
    3. Imitation Learning (HumanCompatibleAI/imitation)
    4. PyTorch-RL (pytorch/rl)
    5. RLlib (ray-project/ray)
    6. CleanRL (vwxyzjn/cleanrl)

    AI recommended 6 alternatives but never named reinforcement-learning-kr/lets-do-irl. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good PyTorch implementations for comparing different inverse reinforcement learning techniques?
    you: not recommended
    AI recommended (in order):
    1. Imitation Learning (imitation)
    2. PyTorch-GAIL
    3. RLkit
    4. MaxEnt-IRL-PyTorch
    5. Awesome-IRL

    AI recommended 5 alternatives but never named reinforcement-learning-kr/lets-do-irl. 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 reinforcement-learning-kr/lets-do-irl?
    pass
    AI did not name reinforcement-learning-kr/lets-do-irl — 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?

  • If a team adopts reinforcement-learning-kr/lets-do-irl in production, what risks or prerequisites should they evaluate first?
    pass
    AI named reinforcement-learning-kr/lets-do-irl 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 reinforcement-learning-kr/lets-do-irl solve, and who is the primary audience?
    pass
    AI named reinforcement-learning-kr/lets-do-irl 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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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite