RRepoGEO

REPOGEO REPORT · LITE

openai/procgen

Default branch master · commit 37b521db · scanned 6/22/2026, 2:36:45 PM

GitHub: 1,167 stars · 221 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE
69 /100
Needs work
Category recall
1 / 2
Avg rank #1.0 when recommended
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 openai/procgen, 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 relevant topics to the repository

    Why:

    COPY-PASTE FIX
    reinforcement-learning, rl, gym-environments, procedural-generation, generalization, benchmark, machine-learning, ai
  • mediumreadme#2
    Emphasize 'generalization benchmark' in the README's opening

    Why:

    CURRENT
    16 simple-to-use procedurally-generated gym environments which provide a direct measure of how quickly a reinforcement learning agent learns generalizable skills.
    COPY-PASTE FIX
    Procgen Benchmark offers 16 simple-to-use procedurally-generated gym environments, specifically designed as a direct measure of how quickly a reinforcement learning agent learns generalizable skills.
  • lowreadme#3
    Add a 'Who is this for?' section to the README

    Why:

    COPY-PASTE FIX
    ## Who is this for?
    
    Procgen Benchmark is primarily for reinforcement learning researchers and practitioners who need:
    *   **Benchmarking generalization:** To evaluate how well RL agents generalize to unseen environments.
    *   **High-speed training:** Fast, procedurally generated environments for efficient experimentation.
    *   **Customizable environments:** The ability to modify or build new environments for specific research questions.

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
1 / 2
50% of queries surface openai/procgen
Avg rank
#1.0
Lower is better. #1 = top recommendation.
Share of voice
8%
Of all named tools, what % are you?
Top rival
Procgen Benchmark
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Procgen Benchmark · recommended 1×
  2. Meta-World · recommended 1×
  3. Gym-MiniGrid · recommended 1×
  4. OpenAI Gym · recommended 1×
  5. NetHack Learning Environment (NLE) · recommended 1×
  • CATEGORY QUERY
    What environments are available for benchmarking reinforcement learning agent generalization?
    you: not recommended
    AI recommended (in order):
    1. Procgen Benchmark
    2. Meta-World
    3. Gym-MiniGrid
    4. OpenAI Gym
    5. NetHack Learning Environment (NLE)
    6. Crafter

    AI recommended 6 alternatives but never named openai/procgen. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking fast, procedurally generated environments for efficient reinforcement learning research and training.
    you: #1
    AI recommended (in order):
    1. Procgen Benchmark (openai/procgen) ← you
    2. MiniGrid (Farama-Foundation/Minigrid)
    3. Gym-Retro (openai/gym-retro)
    4. Unity ML-Agents (Unity-Technologies/ml-agents)
    5. DeepMind Lab (deepmind/lab)
    6. OpenSpiel (deepmind/open_spiel)
    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 openai/procgen?
    pass
    AI named openai/procgen explicitly

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

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

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

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openai/procgen — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite