RRepoGEO

REPOGEO REPORT · LITE

Unity-Technologies/obstacle-tower-env

Default branch master · commit d2450cd5 · scanned 6/11/2026, 7:57:09 AM

GitHub: 546 stars · 123 forks

AI VISIBILITY SCORE
22 /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
1 / 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 Unity-Technologies/obstacle-tower-env, 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
    Strengthen the README's initial positioning to highlight generalization and Unity ML-Agents

    Why:

    CURRENT
    The Obstacle Tower is a procedurally generated environment consisting of multiple floors to be solved by a learning agent.
    COPY-PASTE FIX
    The Obstacle Tower is a procedurally generated 3D environment built with Unity ML-Agents, specifically designed as a challenging benchmark for training and evaluating reinforcement learning agents on generalization, transfer learning, and curriculum learning.
  • mediumhomepage#2
    Add an official project homepage URL

    Why:

    COPY-PASTE FIX
    https://[YOUR_OFFICIAL_OBSTACLE_TOWER_HOMEPAGE_URL_HERE]
  • lowtopics#3
    Add more specific topics related to generalization and benchmarks

    Why:

    CURRENT
    deep-learning, gym-environment, ml-agents, reinforcement-learning, unity-3d
    COPY-PASTE FIX
    deep-learning, gym-environment, ml-agents, reinforcement-learning, unity-3d, generalization-challenge, rl-benchmark, procedural-generation

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 Unity-Technologies/obstacle-tower-env
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
openai/procgen
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. openai/procgen · recommended 1×
  2. Farama-Foundation/MiniGrid · recommended 1×
  3. openai/retro · recommended 1×
  4. deepmind/lab · recommended 1×
  5. Unity-Technologies/ml-agents · recommended 1×
  • CATEGORY QUERY
    What are good environments for training reinforcement learning agents to generalize across varied levels?
    you: not recommended
    AI recommended (in order):
    1. Procgen Benchmark (openai/procgen)
    2. MiniGrid (Farama-Foundation/MiniGrid)
    3. Gym-Retro (openai/retro)
    4. DeepMind Lab (deepmind/lab)
    5. Unity ML-Agents Toolkit (Unity-Technologies/ml-agents)
    6. OpenAI Gym (Farama-Foundation/Gym)

    AI recommended 6 alternatives but never named Unity-Technologies/obstacle-tower-env. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a Unity-based simulation platform to develop and evaluate complex deep reinforcement learning agents.
    you: not recommended
    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 Unity-Technologies/obstacle-tower-env?
    pass
    AI did not name Unity-Technologies/obstacle-tower-env — 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 Unity-Technologies/obstacle-tower-env in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Unity-Technologies/obstacle-tower-env 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 Unity-Technologies/obstacle-tower-env solve, and who is the primary audience?
    pass
    AI did not name Unity-Technologies/obstacle-tower-env — 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?

Embed your GEO score

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MARKDOWN (README)
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Unity-Technologies/obstacle-tower-env — 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