Standardize telemetry and observability practices across Rust projects.
npx skills add https://github.com/edochi/mdvs --skill telemetry-edochi
Please help me install this Agent Skill. Skill: telemetry Source: https://github.com/edochi/mdvs/tree/main/.claude/skills/telemetry Command: npx skills add https://github.com/edochi/mdvs --skill telemetry-edochi
Telemetry and observability conventions to guide adding tracing, logging, metrics, or instrumentation to Rust code, ensuring consistent, actionable diagnostics across a project.
Apply the Telemetry & Observability Conventions to your Rust crate.
High-intent search queries and answers about installing and using this skill.
To establish consistent tracing and log levels in a Rust application, apply standardized telemetry conventions that define when to use error!, warn!, info!, debug!, and trace! macros for actionable diagnostics.
The best way to instrument async functions in Rust without leaking secrets is using the #[instrument] attribute while applying safeguards like skipping sensitive fields to protect data.
Add observability to Rust production services and CLI tools by implementing standardized telemetry rules with tracing primitives, ensuring consistent instrumentation depth across development and production environments.
Use debug! logging in Rust projects for detailed diagnostic information during development, while trace! logging is reserved for extremely verbose step-by-step execution traces to maintain observability.
Yes, you can apply telemetry instrumentation conventions to Rust libraries to ensure consistent observability, structured tracing, and actionable diagnostics across crates and services.
MapleTechLabsConfigure OpenTelemetry tracing, logs, and metrics for Rust services via OTLP HTTP to Maple.
ArieGoldkin...
gar-aiInstrument Rust applications with tracing spans and structured logging for observability.
daidrEnrich event logs with environment data, feature toggles, or tenant identifiers.
