RRepoGEO

REPOGEO REPORT · LITE

GiovanniPasq/agentic-rag-for-dummies

Default branch main · commit ecabc2b2 · scanned 5/13/2026, 3:07:29 PM

GitHub: 3,266 stars · 439 forks

AI VISIBILITY SCORE
28 /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
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 GiovanniPasq/agentic-rag-for-dummies, 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 emphasize 'template' and 'best practices'

    Why:

    CURRENT
    This repository demonstrates how to build an **Agentic RAG (Retrieval-Augmented Generation)** system using LangGraph with minimal code. Most RAG tutorials show basic concepts but lack guidance on building modular, agent-driven systems — this project bridges that gap by providing **both learning materials and an extensible architecture**.
    COPY-PASTE FIX
    This repository provides a **production-ready template** for an **Agentic RAG (Retrieval-Augmented Generation) system** built with LangGraph, showcasing best practices for modular, agent-driven architectures. It serves as both a learning resource and an extensible foundation for your own projects.
  • mediumhomepage#2
    Add a homepage URL to the repository About section

    Why:

    COPY-PASTE FIX
    https://your-project-demo-or-docs-url.com
  • lowcomparison#3
    Add a comparison section to the README

    Why:

    COPY-PASTE FIX
    Add a new section titled 'Comparison to Frameworks' or 'How This Project Relates to X, Y, Z' that explains its role as a concrete implementation built *with* tools like LangGraph, rather than a framework itself.

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 GiovanniPasq/agentic-rag-for-dummies
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. Haystack · recommended 2×
  4. Streamlit · recommended 1×
  5. Gradio · recommended 1×
  • CATEGORY QUERY
    How to build a modular retrieval-augmented generation system with human-in-the-loop clarification?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. Streamlit
    3. Gradio
    4. LlamaIndex
    5. Haystack
    6. OpenAI Assistants API
    7. React
    8. Next.js
    9. FastAPI
    10. Rasa

    AI recommended 10 alternatives but never named GiovanniPasq/agentic-rag-for-dummies. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best practices for quickly building agentic RAG pipelines with local LLMs?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Haystack
    4. LiteLLM
    5. Ollama
    6. LM Studio
    7. Transformers

    AI recommended 7 alternatives but never named GiovanniPasq/agentic-rag-for-dummies. 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 GiovanniPasq/agentic-rag-for-dummies?
    pass
    AI named GiovanniPasq/agentic-rag-for-dummies explicitly

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

  • If a team adopts GiovanniPasq/agentic-rag-for-dummies in production, what risks or prerequisites should they evaluate first?
    pass
    AI named GiovanniPasq/agentic-rag-for-dummies 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 GiovanniPasq/agentic-rag-for-dummies solve, and who is the primary audience?
    pass
    AI did not name GiovanniPasq/agentic-rag-for-dummies — 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?

Embed your GEO score

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GiovanniPasq/agentic-rag-for-dummies — 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