RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/nle

Default branch main · commit 862a439a · scanned 6/1/2026, 1:07:07 PM

GitHub: 982 stars · 129 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 facebookresearch/nle, 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
  • highabout#1
    Update About section to reflect repository's redirect status and new home

    Why:

    CURRENT
    Description: The NetHack Learning Environment
Homepage: (none)
    COPY-PASTE FIX
    Description: ARCHIVED: The NetHack Learning Environment has moved to github.com/heiner/nle.
Homepage: https://github.com/heiner/nle
  • hightopics#2
    Add relevant topics for discoverability

    Why:

    COPY-PASTE FIX
    reinforcement-learning, nethack, ai-environment, deep-learning, procedural-generation, roguelike, game-ai
  • mediumreadme#3
    Add a section to README clarifying the existing license

    Why:

    COPY-PASTE FIX
    Add a new section to the README: `## License
This repository contains a custom license. Please refer to the `LICENSE` file for the specific terms and conditions that apply.`

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 facebookresearch/nle
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Procgen Benchmark
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Procgen Benchmark · recommended 2×
  2. MiniGrid · recommended 1×
  3. Gym-PCGRLE · recommended 1×
  4. NetHack Learning Environment (NLE) · recommended 1×
  5. MineRL · recommended 1×
  • CATEGORY QUERY
    What are good reinforcement learning environments for training agents in procedurally generated games?
    you: not recommended
    AI recommended (in order):
    1. Procgen Benchmark
    2. MiniGrid
    3. Gym-PCGRLE
    4. NetHack Learning Environment (NLE)
    5. MineRL
    6. Obstacle Tower Environment

    AI recommended 6 alternatives but never named facebookresearch/nle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for challenging AI environments to test deep reinforcement learning algorithms on complex decision-making.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym MuJoCo Environments
    2. DeepMind Lab
    3. StarCraft II Learning Environment (SC2LE)
    4. Meta-World
    5. Procgen Benchmark
    6. Google Research Football Environment
    7. Microsoft AirSim

    AI recommended 7 alternatives but never named facebookresearch/nle. 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 facebookresearch/nle?
    pass
    AI named facebookresearch/nle explicitly

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

  • If a team adopts facebookresearch/nle in production, what risks or prerequisites should they evaluate first?
    pass
    AI named facebookresearch/nle 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 facebookresearch/nle solve, and who is the primary audience?
    pass
    AI did not name facebookresearch/nle — 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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facebookresearch/nle — 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