RRepoGEO

REPOGEO REPORT · LITE

PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build

Default branch main · commit bb19628d · scanned 6/17/2026, 7:07:52 AM

GitHub: 662 stars · 252 forks

AI VISIBILITY SCORE
22 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
1 / 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 PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build, 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 opening to clarify it's a book's example code

    Why:

    CURRENT
    # 30 Agents Every AI Engineer Must Build
    
    <a href="https://www.amazon.com/Agents-Every-Engineer-Must-Build/dp/1806109018/ref=sr_1_1?crid=1AESLY0JL95NZ&dib=eyJ2IjoiMSJ9.mmgKkt8jTbpK__ifx3V1MwRYgFwwZicYOQG3zZYSkklSgx7AL2WpW9XJ9No_EjMMNrvw8OQryZ432b8D35N_o84BC7Mffvcf3fI88nJjPu4_NKL1lKn6FE7YH2zZ71PN1kihNO2WOKVcRiyuOlqNq3aSsefSaNIAg7qd9mjbUdCWbdGHUG-onFrgY-wm1QiGhmh6euxsYyo3vBEcLCRWou75m8dIKBbtKDair4ZUe-w.aqhF37h6emt18J8IQQRJH5J3uwAR6q_cfeFlm12rTIA&dib_tag=se&keywords=30+agents+every+ai+engineer+must+build&qid=1775221676&sprefix=30+agent%2Caps%2C114&sr=8-1"></a>
    
    **Build production-ready agent systems using proven architectures and patternsFrom the author of 50 Algorithms Every Programmer Should KnowAuthor:** Imran Ahmad, PhD  
    **Publisher:** Packt Publishing, 2026
    COPY-PASTE FIX
    # 30 Agents Every AI Engineer Must Build
    
    This repository provides the companion code and practical examples for the book '30 Agents Every AI Engineer Must Build' by Imran Ahmad, PhD (Packt Publishing, 2026). It offers hands-on demonstrations for building production-ready AI agent systems using proven architectures and patterns.
  • hightopics#2
    Add specific topics to improve categorization

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    ai-agents, artificial-intelligence, agent-systems, machine-learning, deep-learning, python, book-companion, example-code, packt-publishing, ai-engineering
  • mediumhomepage#3
    Add the book's Amazon page as the repository homepage

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    https://www.amazon.com/Agents-Every-Engineer-Must-Build/dp/1806109018/

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 PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build
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 by deepset · recommended 1×
  4. Microsoft Semantic Kernel · recommended 1×
  5. JADE · recommended 1×
  • CATEGORY QUERY
    How can I build robust AI agent systems for production environments?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack by deepset
    4. Microsoft Semantic Kernel

    AI recommended 4 alternatives but never named PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are common design patterns and architectures for developing intelligent AI agents?
    you: not recommended
    AI recommended (in order):
    1. JADE
    2. NetLogo
    3. GAMA
    4. OpenCog
    5. SOAR
    6. ROS
    7. Fast Downward
    8. LPG
    9. Golog
    10. Jason
    11. AgentSpeak(L)
    12. Stable Baselines3
    13. Ray RLlib
    14. OpenAI Gym
    15. Docker
    16. Kubernetes
    17. Apache Kafka
    18. RabbitMQ

    AI recommended 18 alternatives but never named PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • 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 PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build?
    pass
    AI did not name PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build — 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 PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build in production, what risks or prerequisites should they evaluate first?
    pass
    AI named PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build 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 PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build solve, and who is the primary audience?
    pass
    AI did not name PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build — 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?

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PacktPublishing/30-Agents-Every-AI-Engineer-Must-Build — 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