RRepoGEO

REPOGEO REPORT · LITE

sympozium-ai/sympozium

Default branch main · commit e60a39c9 · scanned 6/12/2026, 7:01:58 AM

GitHub: 526 stars · 62 forks

AI VISIBILITY SCORE
33 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 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 sympozium-ai/sympozium, 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
    Strengthen README's immediate positioning for Kubernetes multi-agent AI

    Why:

    CURRENT
    The current README excerpt shows the core definition 'Sympozium is a coordination layer for multi-agent AI systems on Kubernetes' nested within <p> and <em> tags after a poetic intro.
    COPY-PASTE FIX
    Make the core definition the very first textual content in the README, ideally as an H1 or a prominent, unformatted sentence, e.g., '<h1>Sympozium: The Coordination Layer for Multi-Agent AI on Kubernetes</h1>' or 'Sympozium is the coordination layer for multi-agent AI systems on Kubernetes, providing selective permeability, structured handoffs, and shared memory.'
  • hightopics#2
    Expand repository topics to include Kubernetes and orchestration

    Why:

    CURRENT
    agentic, agentic-ai
    COPY-PASTE FIX
    agentic, agentic-ai, kubernetes, multi-agent, orchestration, ai-agents, coordination
  • mediumcomparison#3
    Add a comparison section to differentiate from common alternatives

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., 'Why Sympozium? (vs. Ray, Kafka, Akka)' or 'Comparison to Alternatives', explaining how Sympozium's focus on multi-agent AI coordination on Kubernetes differs from general distributed systems or actor frameworks.

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 sympozium-ai/sympozium
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
akka/akka
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. akka/akka · recommended 2×
  2. Ray · recommended 1×
  3. Apache Kafka · recommended 1×
  4. Redis · recommended 1×
  5. Akka · recommended 1×
  • CATEGORY QUERY
    How to improve coordination and shared memory for multi-agent AI systems?
    you: not recommended
    AI recommended (in order):
    1. Ray
    2. Apache Kafka
    3. Redis
    4. Akka
    5. ROS
    6. ZeroMQ

    AI recommended 6 alternatives but never named sympozium-ai/sympozium. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are robust solutions for orchestrating multi-agent AI communication on Kubernetes?
    you: not recommended
    AI recommended (in order):
    1. Ray (ray-project/ray)
    2. KubeRay (ray-project/kuberay)
    3. Akka.NET (akkadotnet/akka.net)
    4. Akka (akka/akka)
    5. Akka Cluster (akka/akka)
    6. Akka's Kubernetes Discovery (akka/akka-management)
    7. Dapr (dapr/dapr)
    8. Apache Kafka (apache/kafka)
    9. Strimzi Kafka Operator (strimzi/strimzi-kafka-operator)
    10. NATS.io (nats-io/nats-server)
    11. NATS Operator (nats-io/nats-operator)
    12. OpenFaaS (openfaas/faas)
    13. Knative (knative/serving)

    AI recommended 13 alternatives but never named sympozium-ai/sympozium. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    pass

  • 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 sympozium-ai/sympozium?
    pass
    AI named sympozium-ai/sympozium explicitly

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

  • If a team adopts sympozium-ai/sympozium in production, what risks or prerequisites should they evaluate first?
    pass
    AI named sympozium-ai/sympozium 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 sympozium-ai/sympozium solve, and who is the primary audience?
    pass
    AI did not name sympozium-ai/sympozium — 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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sympozium-ai/sympozium — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
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