What problem does it solve? Go developers at ByteDance need a standardized way to add monitoring instrumentation to services without misusing the underlying metrics v3 library. This Skill provides complete knowledge of the metricx library, which centralizes metric definitions through predefined Metric Models and enforces correct usage via struct tags and lint tooling. ## Core Features & Use Cases - Metric Model Definition: Define all metrics in one struct using Counter, RateCounter, Gauge, Timer, and Histogram types with metric, prefix, tags, and tnames field tags. - Multi-Sink Reporting: Configure simultaneous reporting to ByteDance metrics and InfluxDB via WithFactories, plus global tags, custom namespaces, and time units. - Best Practices & Lint Guidance: Learn DB/cache instrumentation patterns, tag inheritance in nested structs, and how golintx and bytecheck prevent tag misuse. - Use Case: When building a new Go microservice, use this Skill to design a Metric Model for database throughput, latency, and cache hit rates, then initialize metricx with environment tags for production monitoring. ## Quick Start Ask the AI to show how to define a metricx Metric Model with Counter and Timer fields and initialize it with metricx.MustInit for a Go service.
