RRepoGEO

REPOGEO REPORT · LITE

JayLZhou/GraphRAG

Default branch master · commit 4e87938e · scanned 6/18/2026, 9:08:15 PM

GitHub: 1,530 stars · 98 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 JayLZhou/GraphRAG, 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
  • highreadme#1
    Reposition the README's opening paragraph to clarify the project's purpose

    Why:

    CURRENT
    > **GraphRAG** is a popular 🔥🔥🔥 and powerful 💪💪💪 RAG system! 🚀💡 Inspired by systems like Microsoft's, graph-based RAG is unlocking endless possibilities in AI.
    COPY-PASTE FIX
    This project, **DIGIMON**, offers a deep analysis and modularization of **Graph-Based Retrieval-Augmented Generation (RAG) systems**. Inspired by powerful approaches like Microsoft's, our work aims to unveil the underlying mechanisms and share insights into this rapidly evolving field.
  • highlicense#2
    Add a standard open-source license file

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository with the text of the MIT License. Additionally, add a line to the README under a new 'License' section stating: 'This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.'

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 JayLZhou/GraphRAG
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Neo4j
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Neo4j · recommended 2×
  2. Vaticle's TypeDB · recommended 1×
  3. Amazon Neptune · recommended 1×
  4. PyTorch-BigGraph · recommended 1×
  5. OpenKE · recommended 1×
  • CATEGORY QUERY
    How can I enhance RAG system performance by integrating knowledge graphs for retrieval?
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. Vaticle's TypeDB
    3. Amazon Neptune
    4. PyTorch-BigGraph
    5. OpenKE
    6. DGL
    7. LangChain
    8. LlamaIndex
    9. Faiss
    10. Pinecone
    11. Elasticsearch

    AI recommended 11 alternatives but never named JayLZhou/GraphRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for frameworks to analyze and modularize graph-based RAG architectures for better insights.
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. LangGraph (langchain-ai/langgraph)
    3. LlamaIndex (run-llama/llama_index)
    4. Neo4j
    5. Cypher
    6. Graphistry
    7. NetworkX (networkx/networkx)
    8. Pydantic (pydantic/pydantic)

    AI recommended 8 alternatives but never named JayLZhou/GraphRAG. 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 JayLZhou/GraphRAG?
    pass
    AI named JayLZhou/GraphRAG explicitly

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

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