RRepoGEO

REPOGEO REPORT · LITE

circlemind-ai/fast-graphrag

Default branch main · commit 23b3a1be · scanned 5/25/2026, 2:37:29 AM

GitHub: 3,794 stars · 245 forks

AI VISIBILITY SCORE
35 /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
3 / 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 circlemind-ai/fast-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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    graph-rag, rag, retrieval-augmented-generation, llm, graph-database, knowledge-graph, agent-driven, python, fast-rag
  • highreadme#2
    Add a clear H1 title to the README

    Why:

    CURRENT
    <h1 align="center"></h1>
    COPY-PASTE FIX
    <h1 align="center">Fast GraphRAG: High-Performance, Interpretable, Agent-Driven Retrieval Augmented Generation</h1>
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    COPY-PASTE FIX
    https://circlemind.co

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 circlemind-ai/fast-graphrag
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
huggingface/transformers
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. huggingface/transformers · recommended 2×
  2. langchain-ai/langchain · recommended 1×
  3. OpenAI · recommended 1×
  4. Anthropic Claude · recommended 1×
  5. Pinecone · recommended 1×
  • CATEGORY QUERY
    How to build an intelligent RAG system that adapts to diverse data and user queries?
    you: not recommended
    AI recommended (in order):
    1. LangChain (langchain-ai/langchain)
    2. OpenAI
    3. Anthropic Claude
    4. Pinecone
    5. Weaviate (weaviate/weaviate)
    6. LlamaIndex (run-llama/llama_index)
    7. Chroma (chroma-core/chroma)
    8. Qdrant (qdrant/qdrant)
    9. Haystack (deepset-ai/haystack)
    10. Hugging Face Transformers (huggingface/transformers)
    11. Elasticsearch (elastic/elasticsearch)
    12. OpenSearch (opensearch-project/OpenSearch)
    13. Microsoft Azure AI Search
    14. Azure OpenAI Service
    15. Azure Machine Learning
    16. Google Cloud Vertex AI Search and Conversation
    17. Vertex AI Gemini API
    18. Custom Python Scripting
    19. Faiss (facebookresearch/faiss)
    20. Annoy (spotify/annoy)
    21. Transformers (Hugging Face) (huggingface/transformers)

    AI recommended 21 alternatives but never named circlemind-ai/fast-graphrag. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for an efficient and interpretable graph-based RAG framework for agent-driven retrieval.
    you: not recommended
    AI recommended (in order):
    1. Neo4j
    2. LangChain
    3. LlamaIndex
    4. TypeDB
    5. ArangoDB
    6. Amazon Neptune
    7. GraphDB

    AI recommended 7 alternatives but never named circlemind-ai/fast-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
    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 circlemind-ai/fast-graphrag?
    pass
    AI named circlemind-ai/fast-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 circlemind-ai/fast-graphrag in production, what risks or prerequisites should they evaluate first?
    pass
    AI named circlemind-ai/fast-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 circlemind-ai/fast-graphrag solve, and who is the primary audience?
    pass
    AI named circlemind-ai/fast-graphrag explicitly

    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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  • Brand-free category queries5 vs 2 in Lite
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