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Found 350 Skills
Setup Sentry Logging in any project. Use when asked to add Sentry logs, enable structured logging, capture console logs, or integrate logging libraries (Pino, Winston, Loguru) with Sentry. Supports JavaScript, Python, and Ruby.
Enterprise skill for iOS production error observability and logging (iOS 15+, Swift 5.5+). Use this skill when writing or reviewing error handling code, adding logging to iOS apps, replacing print() with os.Logger, configuring crash reporting SDKs (Sentry, Crashlytics, PostHog), fixing silent error patterns (try?, Task {} swallowing errors, Combine pipelines dying), adding privacy annotations to logs, integrating MetricKit, implementing retry logic with observability, handling errors in SwiftUI .task {} modifiers, or auditing catch blocks for proper error reporting. Use this skill any time someone writes a catch block, uses try?, creates a Task {}, sets up error handling, or mentions logging, crash reporting, or error tracking in an iOS context — even if they just say 'add error handling' or 'why is this failing silently.'
Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. Use PROACTIVELY for monitoring infrastructure, performance optimization, or production reliability.
Cloudflare Workers observability with logging, Analytics Engine, Tail Workers, metrics, and alerting. Use for monitoring, debugging, tracing, or encountering log parsing, metric aggregation, alert configuration errors.
Configures structured logging (Serilog/.NET, structlog/Python)
Full Sentry SDK setup for Svelte and SvelteKit. Use when asked to "add Sentry to Svelte", "add Sentry to SvelteKit", "install @sentry/sveltekit", or configure error monitoring, tracing, session replay, or logging for Svelte or SvelteKit applications.
Error handling patterns for robust applications. Use when implementing try-catch blocks, error boundaries, custom errors, or logging. Covers async errors, React error boundaries, and API error responses.
Deploy Docker containers to production with monitoring, logging, and health checks
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
Python Coding Standards, including type hints, logging specifications, naming conventions, code structure, etc. Applicable to all Python code files.
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".
Flutter DevTools, Profiling, Logging & Memory Management