RRepoGEO

REPOGEO REPORT · LITE

inoryy/reaver

Default branch master · commit d7bd7978 · scanned 6/5/2026, 7:02:26 AM

GitHub: 561 stars · 87 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 inoryy/reaver, 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
    Condense and reposition the project's core purpose to the top of the README

    Why:

    CURRENT
    # Reaver: Modular Deep Reinforcement Learning Framework
    
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    ...
    
    **Project status:** No longer maintained!
    Unfortunately, I am no longer able to further develop or provide support to the project.
    
    ## Introduction
    
    Reaver is a modular deep reinforcement learning framework with a focus on various StarCraft II based tasks...
    COPY-PASTE FIX
    # Reaver: Modular Deep Reinforcement Learning Framework
    
    Reaver is a modular deep reinforcement learning framework with a focus on various StarCraft II based tasks, following in DeepMind's footsteps. It supports environments like Gym, Atari, and MuJoCo.
    
    **Project status:** No longer maintained! Unfortunately, I am no longer able to further develop or provide support to the project.
    
    [](https://youtu.be/gEyBzcPU5-w)
    ...
  • mediumhomepage#2
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://youtu.be/gEyBzcPU5-w
  • lowreadme#3
    Consolidate duplicate YouTube links in the README

    Why:

    CURRENT
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    [](https://youtu.be/gEyBzcPU5-w)
    COPY-PASTE FIX
    [Watch the project video here](https://youtu.be/gEyBzcPU5-w)

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 inoryy/reaver
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
AlphaStar
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. AlphaStar · recommended 1×
  2. deepmind/open_spiel · recommended 1×
  3. ray-project/ray · recommended 1×
  4. pytorch/pytorch · recommended 1×
  5. tensorflow/tensorflow · recommended 1×
  • CATEGORY QUERY
    Need a deep reinforcement learning framework to train agents for complex real-time strategy games.
    you: not recommended
    AI recommended (in order):
    1. AlphaStar
    2. OpenSpiel (deepmind/open_spiel)
    3. RLlib (ray-project/ray)
    4. PyTorch (pytorch/pytorch)
    5. TensorFlow (tensorflow/tensorflow)
    6. TF-Agents (tensorflow/agents)
    7. Stable Baselines3 (DLR-RM/stable-baselines3)

    AI recommended 7 alternatives but never named inoryy/reaver. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a modular deep reinforcement learning library supporting various AI research environments.
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. Stable Baselines3
    3. CleanRL
    4. Tianshou
    5. Acme
    6. Catalyst.RL

    AI recommended 6 alternatives but never named inoryy/reaver. 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 inoryy/reaver?
    pass
    AI did not name inoryy/reaver — 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 inoryy/reaver in production, what risks or prerequisites should they evaluate first?
    pass
    AI named inoryy/reaver 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 inoryy/reaver solve, and who is the primary audience?
    pass
    AI named inoryy/reaver explicitly

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

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inoryy/reaver — 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