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Found 62 Skills
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.
PostHog logs for Java
Structured logging for Python applications with context support and powerful processors
Implement observability for Evernote integrations. Use when setting up monitoring, logging, tracing, or alerting for Evernote applications. Trigger with phrases like "evernote monitoring", "evernote logging", "evernote metrics", "evernote observability".
Use when appending structured perf investigation notes and evidence.
Implement comprehensive observability for Guidewire InsuranceSuite including logging, metrics, tracing, and alerting. Trigger with phrases like "guidewire monitoring", "logging guidewire", "metrics", "observability", "alerting", "dashboards guidewire".
Make application behavior visible to coding agents by exposing structured logs and telemetry. Use when asked to "add telemetry", "make logs accessible to agents", "add observability", "debug with logs", or when an agent needs to understand runtime behavior but has no way to query logs. Also use when debugging is difficult because there are no structured logs, when agent docs (CLAUDE.md, AGENTS.md) lack instructions for querying application logs, or when setting up logging infrastructure for a new or existing web application.
OpenTelemetry, structured logging, distributed tracing, alerting, and dashboards
structlog - structured logging library for Python with native JSON support, context binding, and processor pipeline. Integrates with FastAPI, Django, and standard logging module. USE WHEN: user mentions "structlog", "python structured logging", "context binding", asks about "JSON logging python", "fastapi logging", "django structured logging" DO NOT USE FOR: Standard Python logging - use `python-logging` instead, Node.js logging - use `pino` or `winston`, Java logging - use `slf4j` or `logback` instead
Design error handling strategies for TypeScript and Python applications — exception hierarchies, Result/Either types, retry patterns, error boundaries, and structured error logging. Use when designing error handling architecture, choosing between exceptions and Result types, implementing retry logic, or building error recovery flows. Activate on "error handling", "exception hierarchy", "Result type", "retry pattern", "circuit breaker", "error boundary", "Pokemon exception". NOT for debugging specific runtime errors, logging infrastructure setup, or monitoring/alerting configuration.
Structured JSON logging with correlation IDs, request context propagation across async boundaries, performance timing decorators, and worker metrics collection.
Use when adding logging to services, setting up monitoring, creating alerts, debugging production issues, designing SLIs/SLOs, or implementing structured logging (Pino, Winston), metrics (Prometheus, DataDog, CloudWatch), or distributed tracing (OpenTelemetry).