RRepoGEO

REPOGEO REPORT · LITE

RafalWilinski/cloudflare-rag

Default branch main · commit 2f4341bc · scanned 6/9/2026, 11:18:12 PM

GitHub: 602 stars · 90 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
22 /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
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 RafalWilinski/cloudflare-rag, 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
  • highlicense#1
    Add a LICENSE file (e.g., MIT)

    Why:

    CURRENT
    (no LICENSE file detected)
    COPY-PASTE FIX
    Create a LICENSE file in the repository root with the MIT License text.
  • highreadme#2
    Reposition the README's opening to emphasize 'template' and specific use case

    Why:

    CURRENT
    # Fullstack Cloudflare RAG

> This is a fullstack example of how to build a RAG (Retrieval Augmented Generation) app with Cloudflare. It uses Cloudflare Workers, Pages, D1, KV, R2, AI Gateway and Workers AI.
    COPY-PASTE FIX
    # Cloudflare "Chat with your PDFs" RAG Template

> This repository provides a complete, deployable fullstack example of a "Chat with your PDFs" Retrieval Augmented Generation (RAG) application built entirely on Cloudflare. It showcases Cloudflare Workers, Pages, D1, KV, R2, AI Gateway, and Workers AI for a serverless, scalable solution.
  • mediumtopics#3
    Expand repository topics with specific Cloudflare services and application types

    Why:

    CURRENT
    chatgpt, cloudflare, llm, rag
    COPY-PASTE FIX
    cloudflare, llm, rag, serverless, fullstack-app, pdf-chat, workers-ai, cloudflare-workers, cloudflare-pages, cloudflare-d1, cloudflare-kv, cloudflare-r2, vector-search

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 RafalWilinski/cloudflare-rag
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
PostgreSQL
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. PostgreSQL · recommended 2×
  2. AWS Lambda · recommended 2×
  3. LangChain · recommended 1×
  4. FastAPI · recommended 1×
  5. Next.js · recommended 1×
  • CATEGORY QUERY
    How to build a fullstack chat application that can answer questions from PDF documents?
    you: not recommended
    AI recommended (in order):
    1. LangChain
    2. FastAPI
    3. Next.js
    4. PostgreSQL
    5. OpenAI API
    6. Pinecone
    7. ChromaDB
    8. LlamaIndex
    9. Flask
    10. React
    11. MongoDB
    12. Hugging Face Transformers
    13. FAISS
    14. Streamlit
    15. AWS Amplify
    16. AWS Lambda
    17. Amazon S3
    18. Amazon Bedrock
    19. Amazon OpenSearch Service
    20. Google Cloud Platform (GCP)
    21. Firebase
    22. Cloud Functions
    23. Cloud Storage
    24. Vertex AI
    25. AlloyDB for PostgreSQL

    AI recommended 25 alternatives but never named RafalWilinski/cloudflare-rag. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Looking for a serverless architecture to implement hybrid RAG with multiple LLM providers and streaming UI.
    you: not recommended
    AI recommended (in order):
    1. AWS Lambda
    2. Amazon SQS
    3. Amazon Kinesis Data Streams
    4. Amazon DynamoDB
    5. Amazon API Gateway
    6. AWS Step Functions
    7. Google Cloud Functions
    8. Google Cloud Pub/Sub
    9. Google Cloud Firestore
    10. Google Cloud Run
    11. Google Cloud Endpoints
    12. Azure Functions
    13. Azure Service Bus
    14. Azure Cosmos DB
    15. Azure SignalR Service
    16. Azure Logic Apps
    17. Vercel
    18. Netlify
    19. Upstash
    20. Supabase
    21. Cloudflare Workers
    22. OpenFaaS
    23. NATS Streaming
    24. PostgreSQL
    25. Aiven

    AI recommended 25 alternatives but never named RafalWilinski/cloudflare-rag. 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 RafalWilinski/cloudflare-rag?
    pass
    AI did not name RafalWilinski/cloudflare-rag — 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 RafalWilinski/cloudflare-rag in production, what risks or prerequisites should they evaluate first?
    pass
    AI named RafalWilinski/cloudflare-rag 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 RafalWilinski/cloudflare-rag solve, and who is the primary audience?
    pass
    AI did not name RafalWilinski/cloudflare-rag — 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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RafalWilinski/cloudflare-rag — 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