Microservice architectures have become the go-to paradigm for developing scalable distributed systems, offering significant advantages in managing complex applications. However, diagnosing and resolving performance and reliability issues remains a challenge. Traditional centralized telemetry solutions, such as Prometheus, ELK, and cloud platforms like Datadog, require complex configurations and are not specifically tailored to monitor RESTful microservices. Moreover, while the OpenAPI Specification (OAS) is widely used for defining microservice APIs, current telemetry tools do not fully utilize it for improving diagnostics. This paper showcases OAS-Telemetry, a NodeJS package implementing a lightweight, distributed telemetry approach that leverages OAS-based API data. It offers an automated, configuration-free system that streamlines root cause analysis without compromising system performance. The model is designed for the dynamic environment of the Cloud Continuum, where resources and services are dispersed. By allowing telemetry features to be toggled as needed, the proposed tool minimizes performance impact and promotes energy efficiency. Demo video available at https://doi.org/10.5281/zenodo.13905014