Does this skill support Go instrumentation?

Yes, the skill provides specific implementation patterns and code examples for Go, including the use of meters, tracers, and structured loggers.

What standards does this telemetry skill follow?

This skill strictly follows OpenTelemetry (OTel) conventions, ensuring that your metrics, traces, and logs are compatible with industry-standard observability tools.

How are metric names formatted?

Metric names follow a standardized pattern: {service}.{resource}.{measurement}.{unit}, ensuring clarity and easy filtering in dashboards.

Can I validate my telemetry implementation?

Yes, the skill includes references to validation scripts that check if metrics are registered, traces are emitted, and naming conventions are correctly followed.

Telemetry & Observability

Name: Telemetry & Observability
Author: datum-cloud

bydatum-cloud

•

分析与监控

Implements standardized observability including metrics, traces, and logs following OpenTelemetry conventions for Datum Cloud services.

The Telemetry & Observability skill empowers Claude to instrument services with production-grade monitoring capabilities. It focuses on the three pillars of observability—metrics, traces, and logs—ensuring all data follows strict OpenTelemetry conventions for naming and structure. This skill is essential for developers building on Datum Cloud who need to implement distributed request tracking, numeric performance measurements, and structured event logging. It includes guidance on context propagation, attribute mapping, and the use of automated validation scripts to ensure telemetry data is correctly registered and emitted.

主要功能

01OpenTelemetry-compliant instrumentation for metrics, traces, and logs

022 GitHub stars

03Support for Counter, Gauge, and Histogram metric types

04Standardized naming conventions for consistent cross-service monitoring

05Distributed tracing with span attribute management and error recording

06Structured logging patterns with standardized resource and operation fields

使用场景

01Instrumenting a new Go-based microservice for distributed tracing and performance monitoring

02Refactoring legacy logging into structured, OpenTelemetry-compliant event records

03Standardizing metric naming patterns across a complex cloud infrastructure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add datum-cloud/claude-code-plugins capability-telemetry

For use in Claude.ai and ChatGPT

主要功能

01OpenTelemetry-compliant instrumentation for metrics, traces, and logs

022 GitHub stars

03Support for Counter, Gauge, and Histogram metric types

04Standardized naming conventions for consistent cross-service monitoring

05Distributed tracing with span attribute management and error recording

06Structured logging patterns with standardized resource and operation fields

使用场景

01Instrumenting a new Go-based microservice for distributed tracing and performance monitoring

02Refactoring legacy logging into structured, OpenTelemetry-compliant event records

03Standardizing metric naming patterns across a complex cloud infrastructure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add datum-cloud/claude-code-plugins capability-telemetry

For use in Claude.ai and ChatGPT