REPOGEO REPORT · LITE

AutoMQ/automq

Default branch main · commit d3c600e1 · scanned 5/17/2026, 1:21:44 AM

GitHub: 9,868 stars · 707 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 AutoMQ/automq, 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

Add a concise introductory paragraph to the README

Why:

CURRENT

The README's content immediately after the H1 consists of navigation links and social media badges.

COPY-PASTE FIX

Add the following paragraph immediately after the H1, before any links or badges: 'AutoMQ is an open-source, cloud-native message streaming solution that re-architects Apache Kafka to leverage object storage (like AWS S3) as its primary, durable storage layer. It delivers 10x cost savings, instant auto-scaling, and multi-AZ availability for high-volume data workloads, making it ideal for cloud architects and developers seeking a cost-effective, high-performance Kafka alternative or enhancement.'

mediumtopics#2

Expand repository topics with more specific keywords

Why:

CURRENT

automq, diskless, kafka, serverless

COPY-PASTE FIX

automq, diskless, kafka, serverless, message-queue, message-streaming, cloud-native, s3-storage, cost-effective, auto-scaling

mediumreadme#3

Add a comparison section to the README

Why:

COPY-PASTE FIX

Add a new section to the README titled 'Why AutoMQ? (vs. Kafka, Kinesis, Pulsar)' or similar, providing a high-level comparison of AutoMQ's advantages over traditional Kafka, managed Kafka services, and other cloud-native streaming solutions.

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 AutoMQ/automq

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Amazon Kinesis Data Streams

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Amazon Kinesis Data Streams · recommended 2×
Azure Event Hubs · recommended 2×
Google Cloud Pub/Sub · recommended 2×
apache/kafka · recommended 2×
Confluent Cloud · recommended 1×

CATEGORY QUERY
What are cost-effective, auto-scaling message streaming solutions for cloud environments with high data volumes?
you: not recommended
AI recommended (in order):
1. Amazon Kinesis Data Streams
2. Azure Event Hubs
3. Google Cloud Pub/Sub
4. Apache Kafka (apache/kafka)
5. Confluent Cloud
6. Redpanda (redpanda-data/redpanda)
AI recommended 6 alternatives but never named AutoMQ/automq. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking a high-performance, low-latency message queue that leverages object storage for durability and cost savings.
you: not recommended
AI recommended (in order):
1. Apache Kafka (apache/kafka)
2. Apache Pulsar (apache/pulsar)
3. Amazon Kinesis Data Streams
4. Google Cloud Pub/Sub
5. Azure Event Hubs
6. RabbitMQ (rabbitmq/rabbitmq-server)
AI recommended 6 alternatives but never named AutoMQ/automq. 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 AutoMQ/automq?
pass
AI named AutoMQ/automq explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts AutoMQ/automq in production, what risks or prerequisites should they evaluate first?
pass
AI named AutoMQ/automq 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 AutoMQ/automq solve, and who is the primary audience?
pass
AI named AutoMQ/automq explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

Embed your GEO score

Drop this badge into the README of AutoMQ/automq. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/AutoMQ/automq.svg)](https://repogeo.com/en/r/AutoMQ/automq)

HTML

<a href="https://repogeo.com/en/r/AutoMQ/automq"><img src="https://repogeo.com/badge/AutoMQ/automq.svg" alt="RepoGEO" /></a>

Pro

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AutoMQ/automq — 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