RRepoGEO

REPOGEO REPORT · LITE

rll/rllab

Default branch master · commit ba78e4c1 · scanned 5/26/2026, 5:17:22 AM

GitHub: 3,059 stars · 801 forks

AI VISIBILITY SCORE
35 /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
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 rll/rllab, 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 the repository's 'About' description to reflect its legacy status

    Why:

    CURRENT
    rllab is a framework for developing and evaluating reinforcement learning algorithms, fully compatible with OpenAI Gym.
    COPY-PASTE FIX
    rllab is a legacy framework for reinforcement learning research, no longer actively developed. For new projects, please use its actively maintained successor, garage.
  • hightopics#2
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    reinforcement-learning, deep-learning, machine-learning, rl-framework, openai-gym, trpo, policy-gradient, legacy
  • mediumreadme#3
    Add a clear statement about the license(s) in the README

    Why:

    COPY-PASTE FIX
    rllab is released under [Specify License Name(s) here, e.g., 'a custom license based on MIT and Apache 2.0']. Please refer to the LICENSE file for full details.

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 rll/rllab
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
RLlib
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. RLlib · recommended 2×
  2. CleanRL · recommended 2×
  3. Tianshou · recommended 2×
  4. Acme · recommended 2×
  5. Stable Baselines3 · recommended 1×
  • CATEGORY QUERY
    What are good frameworks for developing and evaluating new reinforcement learning algorithms?
    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 rll/rllab. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a robust toolkit to implement and test various deep reinforcement learning agents.
    you: not recommended
    AI recommended (in order):
    1. RLlib
    2. Stable Baselines3 (SB3)
    3. CleanRL
    4. Tianshou
    5. Acme
    6. OpenAI Baselines

    AI recommended 6 alternatives but never named rll/rllab. 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 rll/rllab?
    pass
    AI named rll/rllab explicitly

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

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

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

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rll/rllab — 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