How does this skill help with OpenTelemetry?

It provides specific patterns and mental models for span annotations, helping you determine which attributes to attach to OTel spans to ensure they are useful for future debugging.

What are wide events in observability?

Wide events, or canonical log lines, are single, comprehensive records containing all relevant context—such as user identity, business state, and technical performance—for an operation, optimized for querying rather than just writing.

What is the benefit of high dimensionality?

High dimensionality allows you to add numerous fields to a single event. This enables you to 'slice and dice' your data by any attribute, such as account tier or feature flags, to find specific patterns during an incident.

When should I use the wide-events skill?

Use it when planning new service instrumentation, reviewing code for telemetry coverage, or when you find yourself unable to answer specific questions during a production incident.

Wide Events Observability

Name: Wide Events Observability
Author: front-depiction

byfront-depiction

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Analytics & Monitoring

Guides the implementation of high-dimensionality instrumentation and canonical log lines for superior system observability.

About

This skill provides a conceptual framework and implementation strategy for 'wide events'—comprehensive, structured records that capture full context (business, user, technical, and outcome) within a single span. It helps Claude assist developers in moving away from scattered, low-context logging toward a query-optimized observability strategy using OpenTelemetry. It is particularly useful when designing instrumentation schemas, reviewing span annotations, or debugging complex production incidents where traditional logs fail to provide the necessary context for root cause analysis.

Key Features

Framework for high-dimensionality span annotations including business and user context
Identification of common anti-patterns like technical-only or low-dimensionality logging
Queryability testing to ensure instrumentation answers critical production questions
Strategies for moving from scattered console logs to canonical log lines
7 GitHub stars
Guidance on tail sampling and retention for cost-effective observability

Use Cases

Refactoring existing OpenTelemetry spans to include high-cardinality metadata like User IDs
Auditing observability coverage to ensure incidents are debuggable without code changes
Designing a structured logging and instrumentation strategy for new microservices

About

Key Features

Framework for high-dimensionality span annotations including business and user context
Identification of common anti-patterns like technical-only or low-dimensionality logging
Queryability testing to ensure instrumentation answers critical production questions
Strategies for moving from scattered console logs to canonical log lines
7 GitHub stars
Guidance on tail sampling and retention for cost-effective observability

Use Cases

Refactoring existing OpenTelemetry spans to include high-cardinality metadata like User IDs
Auditing observability coverage to ensure incidents are debuggable without code changes
Designing a structured logging and instrumentation strategy for new microservices