RRepoGEO

REPOGEO REPORT · LITE

DEEP-PolyU/Awesome-GraphRAG

Default branch main · commit 08f26438 · scanned 5/20/2026, 2:18:34 PM

GitHub: 2,385 stars · 204 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
33 /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
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 DEEP-PolyU/Awesome-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

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

OVERALL DIRECTION
  • highreadme#1
    Emphasize the repo as the definitive resource hub in the README intro

    Why:

    CURRENT
    This repository contains a curated list of resources on graph-based retrieval-augmented generation (GraphRAG), which are classified according to "**A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models**". Continuously updating, stay tuned!
    COPY-PASTE FIX
    This repository serves as the definitive, continuously updated hub for comprehensive resources on graph-based retrieval-augmented generation (GraphRAG), meticulously classified according to "**A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Models**". It is designed to be the first stop for anyone seeking surveys, papers, benchmarks, and open-source projects in this field.
  • mediumtopics#2
    Add the 'awesome-list' topic

    Why:

    CURRENT
    graphrag, graphrag-paper, graphrag-survey, knowledge-graph, large-language-models, rag, retrieval-augmented-generation
    COPY-PASTE FIX
    graphrag, graphrag-paper, graphrag-survey, knowledge-graph, large-language-models, rag, retrieval-augmented-generation, awesome-list
  • mediumabout#3
    Enhance the repository description to emphasize its utility as a definitive resource

    Why:

    CURRENT
    Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.
    COPY-PASTE FIX
    Awesome-GraphRAG: The definitive curated list of resources (surveys, papers, benchmarks, and opensource projects) for understanding and advancing graph-based retrieval-augmented generation.

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 DEEP-PolyU/Awesome-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. LlamaIndex · recommended 2×
  3. LangChain · recommended 2×
  4. Microsoft Research · recommended 1×
  5. Towards Data Science · recommended 1×
  • CATEGORY QUERY
    Where can I find comprehensive resources and surveys on graph-based RAG?
    you: not recommended
    AI recommended (in order):
    1. Microsoft Research
    2. Neo4j
    3. Towards Data Science
    4. Medium
    5. LlamaIndex
    6. LangChain
    7. arXiv
    8. GraphAcademy

    AI recommended 8 alternatives but never named DEEP-PolyU/Awesome-GraphRAG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source projects and benchmarks exist for building knowledge graph RAG systems?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. LlamaIndex
    3. Neo4j
    4. neo4j-python-driver
    5. langchain-neo4j
    6. GraphRAG
    7. RDFLib

    AI recommended 7 alternatives but never named DEEP-PolyU/Awesome-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
    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 DEEP-PolyU/Awesome-GraphRAG?
    pass
    AI named DEEP-PolyU/Awesome-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 DEEP-PolyU/Awesome-GraphRAG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named DEEP-PolyU/Awesome-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 DEEP-PolyU/Awesome-GraphRAG solve, and who is the primary audience?
    pass
    AI did not name DEEP-PolyU/Awesome-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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DEEP-PolyU/Awesome-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