Is it compatible with OpenTelemetry standards?

Absolutely. The skill includes patterns for creating custom traces and spans using OpenTelemetry, making it easy to monitor performance in distributed environments.

Does this skill help with Sentry quota management?

Yes, it includes specific patterns and hooks to filter out expected errors like 404s and validation failures, preventing them from consuming your Sentry event quota.

What is the primary benefit of using this observability skill?

It ensures consistent, searchable logs and error reports across your entire stack, which significantly reduces the time spent debugging production issues.

Can I use this for both frontend and backend applications?

Yes, it provides implementation patterns for Pino and Axiom on the backend, as well as Sentry error boundaries and user context tracking for React and App Router frontends.

How does the skill handle request tracing?

It enforces a strict requirement for correlation IDs in every log statement and provides middleware patterns to generate and propagate these IDs across service boundaries.

API Observability with Axiom, Pino & Sentry

Name: API Observability with Axiom, Pino & Sentry
Author: agents-inc

byagents-inc

0•

Analytics & Monitoring

Implements comprehensive observability patterns using Pino for structured logging, Sentry for error tracking, and Axiom for centralized monitoring.

This skill provides a standardized framework for implementing robust observability in Node.js and React applications, focusing on structured logging with Pino, error tracking via Sentry, and high-performance monitoring through Axiom. It enforces best practices such as mandatory correlation IDs for request tracing, automated error boundaries, and OpenTelemetry-based performance spans, ensuring that developers can effectively diagnose issues across complex distributed systems by answering what happened, why it happened, and how to find it.

Key Features

01Structured logging with mandatory correlation IDs for end-to-end request tracing

020 GitHub stars

03Sentry integration with React error boundaries and automated noise filtering

04Log level decision frameworks to optimize production visibility and storage

05Performance tracking with OpenTelemetry custom traces and spans

06Axiom monitoring configuration for real-time alerting on latency and error rates

Use Cases

01Debugging complex request flows across services using unified correlation IDs

02Setting up proactive error tracking and performance monitoring for React applications

03Adding searchable, structured logging to a new API or microservice

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add agents-inc/skills api-observability-axiom-pino-sentry

For use in Claude.ai and ChatGPT

Key Features

01Structured logging with mandatory correlation IDs for end-to-end request tracing

020 GitHub stars

03Sentry integration with React error boundaries and automated noise filtering

04Log level decision frameworks to optimize production visibility and storage

05Performance tracking with OpenTelemetry custom traces and spans

06Axiom monitoring configuration for real-time alerting on latency and error rates

Use Cases

01Debugging complex request flows across services using unified correlation IDs

02Setting up proactive error tracking and performance monitoring for React applications

03Adding searchable, structured logging to a new API or microservice

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add agents-inc/skills api-observability-axiom-pino-sentry

For use in Claude.ai and ChatGPT