RRepoGEO

REPOGEO REPORT · LITE

shariqiqbal2810/MAAC

Default branch master · commit 6174a012 · scanned 6/12/2026, 4:58:06 AM

GitHub: 807 stars · 180 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 shariqiqbal2810/MAAC, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • mediumreadme#1
    Refine the README's opening sentence for clearer positioning

    Why:

    CURRENT
    Code for *Actor-Attention-Critic for Multi-Agent Reinforcement Learning* (Iqbal and Sha, ICML 2019)
    COPY-PASTE FIX
    This repository provides the official PyTorch implementation for the *Actor-Attention-Critic for Multi-Agent Reinforcement Learning* (MAAC) algorithm, as presented in our ICML 2019 paper by Iqbal and Sha.
  • lowhomepage#2
    Add the paper's URL as the repository homepage

    Why:

    COPY-PASTE FIX
    https://proceedings.mlr.press/v97/iqbal19a.html

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 shariqiqbal2810/MAAC
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
ray-project/ray
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ray-project/ray · recommended 2×
  2. deepmind/open_spiel · recommended 2×
  3. oxwhirl/pymarl · recommended 1×
  4. deepmind/acme · recommended 1×
  5. Farama-Foundation/Gymnasium · recommended 1×
  • CATEGORY QUERY
    How to implement multi-agent reinforcement learning with attention mechanisms for coordination?
    you: not recommended
    AI recommended (in order):
    1. RLlib (ray-project/ray)
    2. PyMARL (oxwhirl/pymarl)
    3. OpenSpiel (deepmind/open_spiel)
    4. Acme (deepmind/acme)
    5. Gymnasium (Farama-Foundation/Gymnasium)
    6. PyTorch (pytorch/pytorch)
    7. TensorFlow (tensorflow/tensorflow)

    AI recommended 7 alternatives but never named shariqiqbal2810/MAAC. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a PyTorch-based framework for multi-agent deep reinforcement learning research.
    you: not recommended
    AI recommended (in order):
    1. RLlib (ray-project/ray)
    2. PettingZoo (Farama-Foundation/PettingZoo)
    3. MARLlib (marlbenchmark/MARLlib)
    4. OpenSpiel (deepmind/open_spiel)
    5. CleanRL (vwxyzjn/cleanrl)

    AI recommended 5 alternatives but never named shariqiqbal2810/MAAC. 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 shariqiqbal2810/MAAC?
    pass
    AI named shariqiqbal2810/MAAC explicitly

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

  • If a team adopts shariqiqbal2810/MAAC in production, what risks or prerequisites should they evaluate first?
    pass
    AI named shariqiqbal2810/MAAC 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 shariqiqbal2810/MAAC solve, and who is the primary audience?
    pass
    AI named shariqiqbal2810/MAAC explicitly

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

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shariqiqbal2810/MAAC — 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