Does this skill symbolicate crash reports automatically?

This skill provides the structure to parse MXCallStackTree frames, but symbolication requires your app's specific dSYM files and a symbolication engine.

Can I test MetricKit integrations on the iOS Simulator?

MetricKit only collects data on physical devices. However, this skill includes instructions on how to use 'Simulate MetricKit Payloads' in Xcode to test your code in development.

Which OS versions are covered by this reference?

The reference covers basic metrics from iOS 13, diagnostic payloads from iOS 14, and recent enhancements like launch diagnostics introduced in iOS 16.

Does this skill help with real-time performance debugging?

No, MetricKit is designed for aggregated field data delivered every 24 hours. For real-time profiling, use the 'axiom-performance-profiling' skill with Instruments.

MetricKit API Reference

Name: MetricKit API Reference
Author: CharlesWiltgen

byCharlesWiltgen

•

286

Mobile Development

Provides comprehensive code patterns and API references for implementing Apple's MetricKit to monitor app performance and diagnostics.

About

This skill serves as a detailed technical reference for Apple's MetricKit framework, designed to help developers monitor on-device performance and diagnostic data across iOS, iPadOS, watchOS, and tvOS. It provides ready-to-use implementation patterns for subscriber registration, daily payload handling, and the parsing of complex data structures like MXMetricPayload and MXDiagnosticPayload. Whether you are troubleshooting background exit reasons, analyzing hang durations, or optimizing app launch times, this skill offers the specific guidance needed to integrate robust telemetry and field diagnostics into modern xOS applications.

Key Features

Guidance on MXCallStackTree parsing and preparing data for dSYM symbolication
286 GitHub stars
Implementation patterns for MXMetricManagerSubscriber and early lifecycle registration
Standardized JSON export patterns for uploading metrics to custom analytics backends
Detailed parsing for MXMetricPayload including CPU, memory, and launch histograms
Diagnostic workflows for crash, hang, and disk/CPU exception reporting

Use Cases

Integrating field diagnostics to identify rare, non-reproducible crashes in production
Analyzing app exit reasons like watchdog events and memory pressure (jetsam)
Monitoring battery impact and CPU usage trends across different app versions

About

Key Features

Guidance on MXCallStackTree parsing and preparing data for dSYM symbolication
286 GitHub stars
Implementation patterns for MXMetricManagerSubscriber and early lifecycle registration
Standardized JSON export patterns for uploading metrics to custom analytics backends
Detailed parsing for MXMetricPayload including CPU, memory, and launch histograms
Diagnostic workflows for crash, hang, and disk/CPU exception reporting

Use Cases

Integrating field diagnostics to identify rare, non-reproducible crashes in production
Analyzing app exit reasons like watchdog events and memory pressure (jetsam)
Monitoring battery impact and CPU usage trends across different app versions