RRepoGEO

REPOGEO REPORT · LITE

gensyn-ai/rl-swarm

Default branch main · commit 9c95410b · scanned 5/20/2026, 11:26:48 PM

GitHub: 1,687 stars · 619 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 gensyn-ai/rl-swarm, 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
  • highreadme#1
    Reposition README opening to clearly state core purpose

    Why:

    CURRENT
    > **Note:** There are no official swarms running right now. Please check back later if you're interested in participating in a global, decentralised, crowd-sourced training run or feel free to join a community-owned swarm. Alternatively, explore Delphi, the first live prediction market for machine intelligence.
    COPY-PASTE FIX
    RL Swarm is an open-source, peer-to-peer framework for building and running decentralized, collaborative reinforcement learning (RL) training swarms. It enables models to train together across a distributed network, leveraging collective intelligence for tasks like coding challenges.
  • mediumabout#2
    Enhance About description with key differentiators

    Why:

    CURRENT
    A fully open source framework for creating RL training swarms over the internet.
    COPY-PASTE FIX
    A fully open-source framework for creating decentralized, collaborative reinforcement learning (RL) training swarms over the internet.

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 gensyn-ai/rl-swarm
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Ray RLlib
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Ray RLlib · recommended 1×
  2. Ray · recommended 1×
  3. OpenSpiel · recommended 1×
  4. MPI · recommended 1×
  5. DeepMind Acme · recommended 1×
  • CATEGORY QUERY
    How to set up a distributed system for collaborative reinforcement learning?
    you: not recommended
    AI recommended (in order):
    1. Ray RLlib
    2. Ray
    3. OpenSpiel
    4. MPI
    5. DeepMind Acme
    6. Launchpad
    7. gRPC
    8. TensorFlow Agents (TF-Agents)
    9. TensorFlow Distributed
    10. PyTorch Lightning
    11. PyTorch Distributed
    12. Horovod
    13. MXNet
    14. MPI (Message Passing Interface)
    15. mpi4py

    AI recommended 15 alternatives but never named gensyn-ai/rl-swarm. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an open source framework to run decentralized AI model training experiments.
    you: not recommended
    AI recommended (in order):
    1. PySyft
    2. Flower
    3. OpenFL
    4. FedML
    5. Substra
    6. TensorFlow Federated

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

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

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gensyn-ai/rl-swarm — 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