REPOGEO REPORT · LITE

robustmq/robustmq

Default branch main · commit e2446c10 · scanned 6/18/2026, 2:42:53 PM

GitHub: 1,619 stars · 231 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

40 /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

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 robustmq/robustmq, 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

Reposition the 'About' description for better AI categorization

Why:

CURRENT

Communication infrastructure for the AI era — one binary, one broker, one storage layer, any protocol

COPY-PASTE FIX

A unified, multi-protocol messaging engine for the AI era, built in Rust. One binary, one broker, one storage layer for MQTT, Kafka, NATS, AMQP, and mq9, ideal for AI agent communication and edge deployments.

hightopics#2

Enhance topics with more specific keywords

Why:

CURRENT

agent-communication, ai, ai-agnet, amqp, data, infra, kafka, message, message-queue, middleware, mq, mq9, mqtt, mqtt-broker, queue, rust, serverless, storage, streaming

COPY-PASTE FIX

agent-communication, ai, ai-agnet, amqp, data, infra, kafka, message, message-queue, middleware, mq, mq9, mqtt, mqtt-broker, queue, rust, serverless, storage, streaming, unified-messaging, edge-computing, single-binary, lightweight-mq, ai-agents

mediumreadme#3

Align README H3 with the updated 'About' description

Why:

CURRENT

<h3 align="center">Communication infrastructure for the AI era — one binary, one broker, one storage layer, any protocol</h3>

COPY-PASTE FIX

<h3 align="center">A unified, multi-protocol messaging engine for the AI era, built in Rust. One binary, one broker, one storage layer for MQTT, Kafka, NATS, AMQP, and mq9, ideal for AI agent communication and edge deployments.</h3>

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 robustmq/robustmq

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

apache/kafka

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

apache/kafka · recommended 1×
rabbitmq/rabbitmq-server · recommended 1×
nats-io/nats-server · recommended 1×
zeromq/libzmq · recommended 1×
apache/activemq · recommended 1×

CATEGORY QUERY
What is a unified messaging system for AI agent communication supporting multiple protocols?
you: not recommended
AI recommended (in order):
1. Apache Kafka (apache/kafka)
2. RabbitMQ (rabbitmq/rabbitmq-server)
3. NATS.io (nats-io/nats-server)
4. ZeroMQ (zeromq/libzmq)
5. ActiveMQ (apache/activemq)
AI recommended 5 alternatives but never named robustmq/robustmq. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a lightweight, single-binary message queue written in Rust for edge deployments.
you: not recommended
AI recommended (in order):
1. Redpanda
2. NATS
3. SurrealDB
4. Mosquitto
5. EMQX Nano
6. LiteMQ
7. Kafka
AI recommended 7 alternatives but never named robustmq/robustmq. 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 robustmq/robustmq?
pass
AI named robustmq/robustmq explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts robustmq/robustmq in production, what risks or prerequisites should they evaluate first?
pass
AI named robustmq/robustmq 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 robustmq/robustmq solve, and who is the primary audience?
pass
AI named robustmq/robustmq explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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MARKDOWN (README)

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HTML

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robustmq/robustmq — 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