REPOGEO REPORT · LITE

JetBrains/koog

Default branch develop · commit 0a705578 · scanned 5/25/2026, 4:57:24 PM

GitHub: 4,230 stars · 410 forks

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 JetBrains/koog, 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

Reposition README's immediate opening to clarify core purpose

Why:

CURRENT

The current README excerpt shows badges and links immediately after the H1, before the 'Overview' section.

COPY-PASTE FIX

Move the core definition to be the very first descriptive text after the H1, before any badges or 'Useful links'. For example: '# Koog
Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments.'

mediumreadme#2

Add a 'Comparison' section to the README

Why:

COPY-PASTE FIX

Add a new section to the README, e.g., '## Koog vs. Other Frameworks' that clarifies: 'Koog is a specialized framework for building AI agents, offering multiplatform support and fault tolerance. Unlike general-purpose JVM frameworks (e.g., Spring Boot, Quarkus) or API client generators (e.g., OpenAPI Generator), Koog focuses exclusively on the unique challenges of AI agent development.'

lowabout#3

Condense and sharpen the 'about' description

Why:

CURRENT

Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problems

COPY-PASTE FIX

Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant, and enterprise-ready AI agents across all platforms (JVM, Android, iOS, web). It provides proven solutions for complex LLM and AI problems, leveraging JetBrains' AI product expertise.

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 JetBrains/koog

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Akka

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

Akka · recommended 1×
Quarkus · recommended 1×
Spring Boot · recommended 1×
Micronaut · recommended 1×
Apache Flink · recommended 1×

CATEGORY QUERY
What are the best JVM frameworks for building enterprise-ready, fault-tolerant AI agents?
you: not recommended
AI recommended (in order):
1. Akka
2. Quarkus
3. Spring Boot
4. Micronaut
5. Apache Flink
6. Vert.x
AI recommended 6 alternatives but never named JetBrains/koog. This is the gap to close.
Show full AI answer
CATEGORY QUERY
How to develop multiplatform AI agents for JVM, Android, and iOS using Kotlin?
you: not recommended
AI recommended (in order):
1. Kotlin Multiplatform Mobile
2. TensorFlow Lite
3. Keras
4. ONNX Runtime
5. PyTorch
6. TensorFlow
7. OpenAI API
8. Google Gemini API
9. Hugging Face Inference API
10. Ktor Client
11. OkHttp
12. Kotlinx Serialization
13. Apache MXNet
14. Core ML
15. Deeplearning4j
AI recommended 15 alternatives but never named JetBrains/koog. 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 JetBrains/koog?
pass
AI named JetBrains/koog explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts JetBrains/koog in production, what risks or prerequisites should they evaluate first?
pass
AI named JetBrains/koog 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 JetBrains/koog solve, and who is the primary audience?
pass
AI named JetBrains/koog 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 JetBrains/koog. 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/JetBrains/koog.svg)](https://repogeo.com/en/r/JetBrains/koog)

HTML

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

Pro

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JetBrains/koog — 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