RRepoGEO

REPOGEO REPORT · LITE

embabel/embabel-agent

Default branch main · commit 01a17234 · scanned 5/14/2026, 3:07:52 PM

GitHub: 3,410 stars · 342 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 embabel/embabel-agent, 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 the README's opening paragraph to emphasize production-grade agent orchestration

    Why:

    CURRENT
    Embabel (Em-BAY-bel) is a framework for authoring agentic flows on the JVM that seamlessly mix LLM-prompted interactions with code and domain models. Supports intelligent path finding towards goals. Written in Kotlin but offers a natural usage model from Java. From the creator of Spring.
    COPY-PASTE FIX
    Embabel (Em-BAY-bel) is a robust JVM framework for building production-grade LLM agents and orchestrating complex agentic flows. Designed by the creator of Spring, it seamlessly integrates LLM interactions with your existing code and domain models, enabling intelligent pathfinding towards business goals and predictable behavior for enterprise AI applications.
  • mediumreadme#2
    Add a 'Comparison to Alternatives' section in the README

    Why:

    COPY-PASTE FIX
    ## Comparison to Alternatives

[Add a section here comparing Embabel Agent to frameworks like LangChain4j and Spring AI, highlighting its unique strengths for enterprise-grade, structured, and business-logic-driven agent development on the JVM.]
  • lowexamples#3
    Add a 'Getting Started' or 'Examples' section demonstrating multi-agent orchestration

    Why:

    COPY-PASTE FIX
    ## Getting Started / Examples

[Add a simple, runnable code example demonstrating how to set up and orchestrate multiple LLM-powered agents, ideally showing integration with business logic or domain models.]

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 embabel/embabel-agent
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain4j
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain4j · recommended 2×
  2. Spring AI · recommended 2×
  3. LlamaIndex · recommended 1×
  4. Deeplearning4j (DL4J) · recommended 1×
  5. OkHttp · recommended 1×
  • CATEGORY QUERY
    What frameworks exist for building generative AI agentic flows on the JVM?
    you: not recommended
    AI recommended (in order):
    1. LangChain4j
    2. Spring AI
    3. LlamaIndex
    4. Deeplearning4j (DL4J)
    5. OkHttp
    6. Apache HttpClient
    7. Jackson
    8. Gson
    9. Project Reactor
    10. RxJava
    11. Drools
    12. Camunda
    13. Activiti

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

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Java/Kotlin framework to orchestrate multiple LLM-powered agents with business logic.
    you: not recommended
    AI recommended (in order):
    1. Spring AI
    2. LangChain4j
    3. Quarkus
    4. Micronaut
    5. Apache Camel

    AI recommended 5 alternatives but never named embabel/embabel-agent. 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 embabel/embabel-agent?
    pass
    AI did not name embabel/embabel-agent — 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 embabel/embabel-agent in production, what risks or prerequisites should they evaluate first?
    pass
    AI named embabel/embabel-agent 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 embabel/embabel-agent solve, and who is the primary audience?
    pass
    AI named embabel/embabel-agent explicitly

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

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite