RRepoGEO

REPOGEO REPORT · LITE

google/adk-go

Default branch main · commit bfab1bd7 · scanned 6/18/2026, 3:46:39 AM

GitHub: 8,182 stars · 714 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 google/adk-go, 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
    Remove HTML structure from README's opening section

    Why:

    CURRENT
    <html>
        <h2 align="center">
          
        </h2>
        <h3 align="center">
          An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
        </h3>
        <h3 align="center">
          Important Links:
          <a href="https://google.github.io/adk-docs/">Docs</a> &
          <a href="https://github.com/google/adk-go/tree/main/examples">Samples</a> &
          <a href="https://github.com/google/adk-python">Python ADK</a> &
          <a href="https://github.com/google/adk-java">Java ADK</a> & 
          <a href="https://github.com/google/adk-web">ADK Web</a>.
        </h3>
    </html>
    COPY-PASTE FIX
    An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
    
    Important Links: [Docs](https://google.github.io/adk-docs/) & [Samples](https://github.com/google/adk-go/tree/main/examples) & [Python ADK](https://github.com/google/adk-python) & [Java ADK](https://github.com/google/adk-java) & [ADK Web](https://github.com/google/adk-web).
  • highreadme#2
    Reposition and clarify the core description in the README's opening

    Why:

    CURRENT
    An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
    COPY-PASTE FIX
    # Agent Development Kit (ADK) for Go
    
    An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated **Large Language Model (LLM) agents** and **Generative AI systems** with flexibility and control. This ADK (Agent Development Kit) is designed for AI agent development, distinct from any Android-related kits.
  • mediumcomparison#3
    Add a 'Comparison with other Go LLM frameworks' section to README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., `## 🆚 ADK vs. Other Go LLM Frameworks`, outlining how ADK-Go differentiates itself from `LangChain Go`, `Go-LLM`, or `Gollum` in terms of philosophy, features, or use cases.

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 google/adk-go
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
tmc/langchaingo
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. tmc/langchaingo · recommended 1×
  2. go-llm/llm · recommended 1×
  3. gollum-ai/gollum · recommended 1×
  4. sashabaranov/go-openai · recommended 1×
  5. go-transformers/transformers · recommended 1×
  • CATEGORY QUERY
    What are the best Go frameworks for developing and evaluating large language model agents?
    you: not recommended
    AI recommended (in order):
    1. LangChain Go (tmc/langchaingo)
    2. Go-LLM (go-llm/llm)
    3. Gollum (gollum-ai/gollum)
    4. OpenAI Go Library (sashabaranov/go-openai)
    5. Hugging Face Transformers Go (go-transformers/transformers)
    6. Your Own Custom Framework

    AI recommended 6 alternatives but never named google/adk-go. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a Go toolkit for creating and managing complex multi-agent AI systems effectively.
    you: not recommended
    AI recommended (in order):
    1. Akka.NET (akkadotnet/akka.net)
    2. Asynq (hibiken/asynq)
    3. Go standard library
    4. Ants (panjf2000/ants)
    5. gRPC (grpc/grpc-go)

    AI recommended 5 alternatives but never named google/adk-go. 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 google/adk-go?
    pass
    AI named google/adk-go explicitly

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

  • If a team adopts google/adk-go in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google/adk-go 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 google/adk-go solve, and who is the primary audience?
    pass
    AI named google/adk-go explicitly

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

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google/adk-go — 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