Does this skill help with performance monitoring?

Yes, by integrating OpenTelemetry and Sentry's performance features, it allows you to track request latency, database query performance, and distributed traces.

Can I use this for Next.js applications?

Yes, the skill includes asset structures specifically designed for Next.js, including client, server, and edge runtime configurations for Sentry and PostHog.

What is the 'AdonisJS-inspired' exception pattern?

It is a design pattern where custom exception classes are 'self-handling' (knowing how to format their own HTTP response) and 'self-reporting' (knowing how to log themselves), which decentralizes error logic from main controllers.

What core tools are supported by this skill?

The skill provides patterns and configurations for Sentry (errors), PostHog (analytics), Pino (logging), and OpenTelemetry (metrics and tracing).

Why use structured logging like Pino instead of console.log?

Structured logging outputs data in JSON format, making it far easier to search, filter, and analyze using log management tools like Datadog, ELK, or BetterStack.

Monitoring & Observability

Name: Monitoring & Observability
Author: leobrival

byleobrival

0•

Analytics & Monitoring

Configures a complete observability stack including error tracking, product analytics, and structured logging using industry-standard tools.

This skill enables Claude to implement a robust monitoring and observability architecture within modern applications. It provides a standardized approach to error tracking with Sentry, product analytics via PostHog, and high-performance structured logging with Pino. By utilizing an AdonisJS-inspired exception handling pattern, it ensures that errors are self-reporting and self-handling, leading to cleaner codebases and faster debugging. It also supports OpenTelemetry for vendor-agnostic metrics and tracing, making it ideal for developers building production-grade, traceable systems that require deep insight into application health and user behavior.

Key Features

01Vendor-agnostic metrics and tracing using OpenTelemetry

02Standardized error tracking and session replay with Sentry

03Self-handling, AdonisJS-inspired custom exception patterns for cleaner APIs

04Structured JSON logging for high-performance analysis with Pino

05Product analytics and feature flag implementation via PostHog

060 GitHub stars

Use Cases

01Implementing event tracking and product analytics to gain user behavior insights

02Setting up a centralized error handling and reporting system for a Node.js or Next.js API

03Transitioning from basic console logs to structured, searchable JSON logging for production monitoring

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add leobrival/topographic-studio-plugins monitoring-observability

For use in Claude.ai and ChatGPT

Download Skill