RRepoGEO

REPOGEO REPORT · LITE

emarco177/langchain-course

Default branch main · commit 5df9a3fe · scanned 6/23/2026, 6:38:43 AM

GitHub: 1,480 stars · 2,803 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
27 /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
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 emarco177/langchain-course, 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 the README's opening sentence to clearly state it's a project-based course repository

    Why:

    CURRENT
    Learn LangChain and LangGraph by building real world AI Agents (Python, Latest Version V.1.0+)
    COPY-PASTE FIX
    This repository serves as a project-based course to learn LangChain and LangGraph by building real-world AI Agents (Python, Latest Version V.1.0+).
  • mediumtopics#2
    Add topics that categorize the repo as a learning resource or course

    Why:

    CURRENT
    agents, langchain, langgraph, langsmith, python, rag
    COPY-PASTE FIX
    agents, langchain, langgraph, langsmith, python, rag, course, tutorial, learning-resource, project-based-learning
  • lowreadme#3
    Harmonize the number of projects mentioned in the README's introduction and the 'What You'll Build' section

    Why:

    CURRENT
    Build 3 end-to-end working LangChain based generative AI applications
    COPY-PASTE FIX
    Build 7 end-to-end working LangChain based generative AI applications

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 emarco177/langchain-course
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. DeepLearning.AI · recommended 1×
  3. AWS · recommended 1×
  4. Udemy · recommended 1×
  5. Coursera · recommended 1×
  • CATEGORY QUERY
    Where can I find a project-based guide to develop advanced AI agents using Python?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. DeepLearning.AI
    3. AWS
    4. Udemy
    5. Coursera
    6. Manning Publications
    7. Awesome-LLM-Agents (Paitesanshi/awesome-llm-agents)
    8. AutoGen (microsoft/autogen)
    9. CrewAI (joaomdmoura/crewai)

    AI recommended 9 alternatives but never named emarco177/langchain-course. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best libraries for building intelligent search agents and RAG systems?
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack
    4. Faiss
    5. Weaviate
    6. Pinecone
    7. Qdrant
    8. Chroma
    9. Milvus
    10. Sentence-Transformers

    AI recommended 10 alternatives but never named emarco177/langchain-course. 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 emarco177/langchain-course?
    pass
    AI did not name emarco177/langchain-course — 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 emarco177/langchain-course in production, what risks or prerequisites should they evaluate first?
    pass
    AI named emarco177/langchain-course 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 emarco177/langchain-course solve, and who is the primary audience?
    pass
    AI did not name emarco177/langchain-course — 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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emarco177/langchain-course — 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