RRepoGEO

REPOGEO REPORT · LITE

dabit3/gpt-travel-advisor

Default branch main · commit 03f24bcd · scanned 6/14/2026, 3:18:55 AM

GitHub: 551 stars · 111 forks

AI VISIBILITY SCORE
28 /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
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 dabit3/gpt-travel-advisor, 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 the README to clearly state the project's purpose and audience

    Why:

    CURRENT
    # GPT Travel advisor
    COPY-PASTE FIX
    # GPT Travel Advisor: A Reference Architecture for AI-Powered Travel Planning
    
    This repository provides a full-stack, serverless reference architecture for building personalized travel applications using GPT-3 and AWS Amplify. It offers a comprehensive blueprint for developers looking to integrate large language models into intelligent travel planning solutions.
  • highlicense#2
    Add a LICENSE file and mention it in the README

    Why:

    COPY-PASTE FIX
    Create a `LICENSE` file in the root of the repository containing the text of the MIT License. Additionally, add a line to the README, for example: `## License
    This project is open-sourced under the MIT License.`
  • mediumhomepage#3
    Add a homepage URL to the repository's About section

    Why:

    COPY-PASTE FIX
    Add a link to a live demo or project page in the repository's 'About' section (e.g., `https://gpt-travel-advisor.dabit3.com` if one exists, or a placeholder if not yet deployed).

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 dabit3/gpt-travel-advisor
Avg rank
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Scikit-learn
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Scikit-learn · recommended 2×
  2. OpenAI GPT · recommended 1×
  3. Google Cloud AI Platform · recommended 1×
  4. Vertex AI · recommended 1×
  5. LangChain · recommended 1×
  • CATEGORY QUERY
    How can I create an AI-driven travel itinerary generator for users?
    you: not recommended
    AI recommended (in order):
    1. OpenAI GPT
    2. Google Cloud AI Platform
    3. Vertex AI
    4. LangChain
    5. Google Maps Platform
    6. Places API
    7. Directions API
    8. Amadeus for Developers
    9. Skyscanner API
    10. Kayak API
    11. Neo4j
    12. Scikit-learn

    AI recommended 12 alternatives but never named dabit3/gpt-travel-advisor. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are some good reference architectures for building intelligent travel planning applications?
    you: not recommended
    AI recommended (in order):
    1. Amazon API Gateway
    2. Azure API Management
    3. Google Cloud Endpoints
    4. AWS Lambda
    5. Azure Functions
    6. Google Cloud Functions
    7. Amazon ECS
    8. Amazon EKS
    9. Azure Kubernetes Service (AKS)
    10. Google Kubernetes Engine (GKE)
    11. Amazon SQS
    12. Amazon Kinesis
    13. Azure Service Bus
    14. Azure Event Hubs
    15. Google Cloud Pub/Sub
    16. Amazon DynamoDB
    17. Amazon Aurora
    18. Azure Cosmos DB
    19. Google Cloud Firestore
    20. Google Cloud Spanner
    21. Amazon SageMaker
    22. Amazon Personalize
    23. Amazon Comprehend
    24. Azure Machine Learning
    25. Azure Cognitive Services
    26. Google AI Platform
    27. Google Cloud Natural Language API
    28. Amazon OpenSearch Service
    29. Elasticsearch
    30. Algolia
    31. Amazon EventBridge
    32. Amazon S3
    33. Amazon Cognito
    34. Amazon Location Service
    35. Django
    36. Spring Boot
    37. PostgreSQL
    38. MySQL
    39. TensorFlow
    40. PyTorch
    41. Scikit-learn
    42. Hugging Face Transformers
    43. Redis
    44. Apache Kafka
    45. Apache Flink
    46. Apache Spark Streaming
    47. AWS Kinesis Data Analytics
    48. Apache Cassandra
    49. MongoDB
    50. Apache Mahout
    51. Kubernetes
    52. OpenShift
    53. Rancher
    54. Oracle Database
    55. Azure Blob Storage
    56. Amazon CloudFront
    57. Azure CDN

    AI recommended 57 alternatives but never named dabit3/gpt-travel-advisor. 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 dabit3/gpt-travel-advisor?
    pass
    AI did not name dabit3/gpt-travel-advisor — 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 dabit3/gpt-travel-advisor in production, what risks or prerequisites should they evaluate first?
    pass
    AI named dabit3/gpt-travel-advisor 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 dabit3/gpt-travel-advisor solve, and who is the primary audience?
    pass
    AI named dabit3/gpt-travel-advisor 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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