RRepoGEO

REPOGEO REPORT · LITE

google/adk-samples

Default branch main · commit ca6776f8 · scanned 5/21/2026, 8:14:01 AM

GitHub: 9,357 stars · 2,553 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-samples, 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
    Clarify 'ADK' acronym and its domain in README intro

    Why:

    CURRENT
    Welcome to the ADK Sample Agents repository! This collection provides ready-to-use agents built on top of Agent Development Kit, designed to accelerate your development process. These agents cover a range of common use cases and complexities, from simple conversational bots to complex multi-agent workflows.
    COPY-PASTE FIX
    Welcome to the ADK Sample Agents repository! This collection provides ready-to-use agents built on top of the **Agent Development Kit (ADK) for AI and conversational systems**, designed to accelerate your development process. These agents cover a range of common use cases and complexities, from simple conversational bots to complex multi-agent workflows.
  • hightopics#2
    Add specific topics for AI agents and conversational AI

    Why:

    CURRENT
    adk, agent-samples, agents
    COPY-PASTE FIX
    adk, agent-samples, agents, ai-agents, conversational-ai, llm-agents, multi-agent-systems, bot-development, google-adk
  • mediumabout#3
    Enhance repository description to clarify 'ADK' and its domain

    Why:

    CURRENT
    A collection of sample agents built with Agent Development Kit (ADK)
    COPY-PASTE FIX
    A collection of sample AI agents built with Google's Agent Development Kit (ADK) for conversational and intelligent systems.

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-samples
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 1×
  2. LlamaIndex · recommended 1×
  3. Haystack · recommended 1×
  4. Rasa · recommended 1×
  5. Microsoft Bot Framework · recommended 1×
  • CATEGORY QUERY
    What are the best frameworks for building AI agents and conversational bots?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. Rasa
    5. Microsoft Bot Framework
    6. Google Dialogflow
    7. OpenAI Assistants API

    AI recommended 7 alternatives but never named google/adk-samples. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need ready-to-use code examples for developing intelligent agents across multiple languages.
    you: not recommended
    AI recommended (in order):
    1. OpenAI Gym
    2. Stable Baselines3
    3. TensorFlow Agents
    4. RLlib
    5. Microsoft Cognitive Toolkit (CNTK)
    6. DeepMind Lab
    7. Unity ML-Agents

    AI recommended 7 alternatives but never named google/adk-samples. 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-samples?
    pass
    AI named google/adk-samples 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-samples in production, what risks or prerequisites should they evaluate first?
    pass
    AI named google/adk-samples 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-samples solve, and who is the primary audience?
    pass
    AI named google/adk-samples 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-samples — 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