RRepoGEO

REPOGEO REPORT · LITE

Sunagatov/Iced-Latte

Default branch development · commit d9c3029c · scanned 6/17/2026, 9:12:20 AM

GitHub: 635 stars · 135 forks

AI VISIBILITY SCORE
40 /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
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 Sunagatov/Iced-Latte, 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
    Add a disambiguation note to the README

    Why:

    CURRENT
    The README starts with '☕ Production-grade Java 25 / Spring Boot 4 backend for a coffee marketplace.'
    COPY-PASTE FIX
    Add the following sentence prominently near the top of the README: 'Note: This project is a Java/Spring Boot backend for a coffee marketplace and is not related to the Rust Iced GUI framework.'
  • mediumtopics#2
    Expand topics with domain-specific keywords

    Why:

    CURRENT
    docker, java, jwt, kubernetes, log4j2, lombok, maven, postgresql-database, postman, sonarqube, spring-boot, spring-data-jpa, stripe
    COPY-PASTE FIX
    docker, java, jwt, kubernetes, log4j2, lombok, maven, postgresql-database, postman, sonarqube, spring-boot, spring-data-jpa, stripe, e-commerce, retail, marketplace, coffee-shop, backend, microservices, payment-gateway, authentication, order-management, product-catalog
  • lowlicense#3
    Clarify license type in README

    Why:

    COPY-PASTE FIX
    Add a sentence to the README, for example in a 'License' section: 'This project is licensed under a custom or compound license, as detailed in the [LICENSE](LICENSE) file.'

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 Sunagatov/Iced-Latte
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Kubernetes
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Kubernetes · recommended 2×
  2. ELK Stack · recommended 2×
  3. OAuth 2.0 · recommended 2×
  4. Amazon Web Services (AWS) · recommended 1×
  5. Amazon EC2 · recommended 1×
  • CATEGORY QUERY
    How to build a scalable e-commerce backend with Java Spring Boot and cloud deployment?
    you: not recommended
    AI recommended (in order):
    1. Amazon Web Services (AWS)
    2. Amazon EC2
    3. Amazon RDS
    4. Amazon S3
    5. Amazon SQS
    6. Amazon SNS
    7. Amazon ElastiCache
    8. AWS Lambda
    9. Google Cloud Platform (GCP)
    10. Google Compute Engine
    11. Cloud SQL
    12. Cloud Storage
    13. Cloud Pub/Sub
    14. Memorystore
    15. Cloud Functions
    16. GKE (Google Kubernetes Engine)
    17. Microsoft Azure
    18. Azure Virtual Machines
    19. Azure SQL Database
    20. Azure Blob Storage
    21. Azure Service Bus
    22. Azure Cache for Redis
    23. Azure Functions
    24. PostgreSQL
    25. AWS RDS for PostgreSQL
    26. Google Cloud SQL for PostgreSQL
    27. Azure Database for PostgreSQL
    28. Amazon DynamoDB
    29. Google Cloud Firestore
    30. Azure Cosmos DB
    31. Redis
    32. Amazon ElastiCache for Redis
    33. Google Cloud Memorystore for Redis
    34. Apache Kafka
    35. Amazon MSK
    36. Confluent Cloud
    37. Aiven for Apache Kafka
    38. Amazon SQS (Simple Queue Service)
    39. RabbitMQ
    40. Spring Cache Abstraction
    41. Caffeine (ben-manes/caffeine)
    42. Amazon API Gateway
    43. Google Cloud Endpoints
    44. Azure API Management
    45. AWS Application Load Balancer (ALB)
    46. Google Cloud Load Balancing
    47. Azure Load Balancer
    48. Kubernetes
    49. Amazon EKS
    50. Google Kubernetes Engine (GKE)
    51. Azure Kubernetes Service (AKS)
    52. AWS Fargate
    53. Amazon ECS
    54. Docker Compose (docker/compose)
    55. Prometheus (prometheus/prometheus)
    56. Grafana (grafana/grafana)
    57. Micrometer (micrometer-metrics/micrometer)
    58. ELK Stack
    59. Elasticsearch (elastic/elasticsearch)
    60. Logstash (elastic/logstash)
    61. Kibana (elastic/kibana)
    62. EFK Stack
    63. Fluentd (fluent/fluentd)
    64. AWS CloudWatch
    65. Google Cloud Monitoring
    66. Azure Monitor
    67. Spring Security (spring-projects/spring-security)
    68. OAuth 2.0
    69. OpenID Connect
    70. Auth0
    71. Okta
    72. AWS Cognito
    73. AWS WAF (Web Application Firewall)
    74. Google Cloud Armor
    75. Azure Application Gateway with WAF
    76. CloudFront

    AI recommended 76 alternatives but never named Sunagatov/Iced-Latte. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good Java microservices examples for retail platforms with authentication and payment integration?
    you: not recommended
    AI recommended (in order):
    1. Spring PetClinic Microservices
    2. Spring Boot
    3. Spring Cloud
    4. Eureka
    5. Zuul
    6. Spring Cloud Gateway
    7. Spring Security
    8. JHipster
    9. Angular
    10. React
    11. Vue
    12. JWT
    13. OAuth 2.0
    14. Consul
    15. Axon Framework
    16. Quarkus
    17. Kubernetes
    18. Spring Cloud Config
    19. Resilience4j
    20. Hystrix
    21. Sleuth
    22. Zipkin
    23. OpenTelemetry
    24. Micrometer
    25. Prometheus
    26. ELK Stack
    27. Stripe
    28. PayPal
    29. Adyen

    AI recommended 29 alternatives but never named Sunagatov/Iced-Latte. 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 Sunagatov/Iced-Latte?
    pass
    AI named Sunagatov/Iced-Latte explicitly

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

  • If a team adopts Sunagatov/Iced-Latte in production, what risks or prerequisites should they evaluate first?
    pass
    AI named Sunagatov/Iced-Latte 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 Sunagatov/Iced-Latte solve, and who is the primary audience?
    pass
    AI named Sunagatov/Iced-Latte explicitly

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

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Sunagatov/Iced-Latte — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite