RRepoGEO

REPOGEO REPORT · LITE

Raudaschl/rag-fusion

Default branch master · commit e6ae2d44 · scanned 5/28/2026, 10:03:17 AM

GitHub: 938 stars · 113 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 Raudaschl/rag-fusion, 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 H1 to specify project type

    Why:

    CURRENT
    # RAG-Fusion: The Next Frontier of Search Technology
    COPY-PASTE FIX
    # Raudaschl/rag-fusion: A Python Library for Advanced RAG Retrieval
  • highreadme#2
    Add a direct "What this repo provides" statement to README

    Why:

    COPY-PASTE FIX
    Add this sentence to the first paragraph of the Overview: "This repository provides a Python library and evaluation harness for implementing and benchmarking RAG-Fusion."
  • mediumhomepage#3
    Add a homepage URL to the repository metadata

    Why:

    CURRENT
    (none)
    COPY-PASTE FIX
    Add the URL of the article "Forget RAG, the Future is RAG-Fusion" as the repository homepage.

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 Raudaschl/rag-fusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
HyDE
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. HyDE · recommended 1×
  2. GPT-4 · recommended 1×
  3. Claude 3 Opus · recommended 1×
  4. WordNet · recommended 1×
  5. Word2Vec · recommended 1×
  • CATEGORY QUERY
    How to improve RAG system retrieval quality when user queries are ambiguous or mismatched?
    you: not recommended
    AI recommended (in order):
    1. HyDE
    2. GPT-4
    3. Claude 3 Opus
    4. WordNet
    5. Word2Vec
    6. GloVe
    7. FastText
    8. Sentence Transformers (UKP-LAB/sentence-transformers)
    9. all-MiniLM-L6-v2
    10. msmarco-distilbert-base-v4
    11. BM25
    12. Cohere Embed v3
    13. OpenAI Embeddings
    14. text-embedding-3-large
    15. Elasticsearch (elastic/elasticsearch)
    16. Pinecone
    17. Weaviate (weaviate/weaviate)
    18. Cross-Encoders
    19. cross-encoder/ms-marco-MiniLM-L-6-v2
    20. GPT-3.5
    21. Llama 3

    AI recommended 21 alternatives but never named Raudaschl/rag-fusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for Python libraries that enhance RAG with advanced query reformulation and result fusion.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex
    2. LangChain
    3. Haystack (deepset/Haystack)
    4. RAGatouille
    5. Sentence-Transformers
    6. Rank_BM25
    7. Cohere API

    AI recommended 7 alternatives but never named Raudaschl/rag-fusion. 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 Raudaschl/rag-fusion?
    pass
    AI named Raudaschl/rag-fusion explicitly

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

  • If a team adopts Raudaschl/rag-fusion in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Raudaschl/rag-fusion 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 Raudaschl/rag-fusion solve, and who is the primary audience?
    pass
    AI named Raudaschl/rag-fusion 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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MARKDOWN (README)
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Raudaschl/rag-fusion — 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