Use when adding Spring AI-specific model observations, token usage, latency, externally configured cost attribution, advisor telemetry, or protected prompt and completion logging. Use production-observability for general service metrics, health, logs, and…
Use when packaging a Spring Boot 3 application as an OCI image or GraalVM native executable. Covers buildpacks, layered images, JVM containers, AOT hints, probes, security, and verification.
Use when implementing Kafka, RabbitMQ, Pulsar, or JMS producers and consumers in Spring Boot 3. Covers event contracts, idempotency, retries, dead-letter handling, ordering, and outbox delivery.
Use when exposing Spring Boot 3 application capabilities through Model Context Protocol tools, resources, or prompts. Covers Spring AI 1.x tool callback registration, transports, schemas, errors, security, and standalone MCP Java SDK compatibility.
Use when working in a multi-module Maven project. Covers parent POM conventions, shared dependency management, inter-module rules, and build ordering.
Use when implementing tenant resolution, database or schema isolation, tenant-aware JPA, reactive tenant context, migrations, caching, jobs, or authorization in Spring Boot 3.
Use when adding service-wide Spring Boot 3 Actuator, Micrometer metrics, distributed tracing, OpenTelemetry export, structured logging, health probes, dashboards, or alerts. Combine with ai-observability only for Spring AI-specific token, prompt, and model…
Use when generating REST controllers, DTOs, success response contracts, pagination, HTTP status mapping, or API versioning. For RFC 9457 exception and error response formatting, use problem-details-rfc9457 unless the project explicitly requires a legacy error…