RRepoGEO

REPOGEO REPORT · LITE

evoiz/Agentic-Design-Patterns

Default branch main · commit 11835e4e · scanned 6/18/2026, 12:57:30 AM

GitHub: 1,641 stars · 295 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
23 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 0 warn · 1 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 evoiz/Agentic-Design-Patterns, 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

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highabout#1
    Add a concise repository description

    Why:

    COPY-PASTE FIX
    A comprehensive guide and code repository for Agentic Design Patterns, offering hands-on learning to build intelligent AI agent systems.
  • highlicense#2
    Create a LICENSE file for the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file in the repository root, for example, using the MIT License for the code examples, and ensure the book's copyright is clearly stated within the book itself or the README.

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 evoiz/Agentic-Design-Patterns
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
LangChain
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. LangChain · recommended 2×
  2. LlamaIndex · recommended 2×
  3. AutoGen · recommended 2×
  4. CrewAI · recommended 2×
  5. Haystack · recommended 2×
  • CATEGORY QUERY
    How can I learn agentic design patterns for building robust AI systems?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. AutoGen
    4. CrewAI
    5. Haystack
    6. OpenAI Assistants API

    AI recommended 6 alternatives but never named evoiz/Agentic-Design-Patterns. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are practical techniques for developing intelligent AI agents, including RAG and multi-agent systems?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. AutoGen
    5. CrewAI
    6. Open Interpreter
    7. Instructor

    AI recommended 7 alternatives but never named evoiz/Agentic-Design-Patterns. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    fail

    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 evoiz/Agentic-Design-Patterns?
    pass
    AI named evoiz/Agentic-Design-Patterns explicitly

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

  • If a team adopts evoiz/Agentic-Design-Patterns in production, what risks or prerequisites should they evaluate first?
    pass
    AI named evoiz/Agentic-Design-Patterns 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 evoiz/Agentic-Design-Patterns solve, and who is the primary audience?
    pass
    AI did not name evoiz/Agentic-Design-Patterns — 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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evoiz/Agentic-Design-Patterns — 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