# Observability

> Observability - logging, metrics, tracing. Use when adding monitoring.

- Skill: `sylphxai/observability` (Agent Skill)
- Install (CLI): `npx skillmds@latest add sylphxai/observability`
- Raw SKILL.md: https://api.skillmd.com/api/skills/sylphxai/observability/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: SylphxAI (https://skillmd.com/u/sylphxai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/sylphxai/observability

---


# Observability Guideline

## Tech Stack

* **Error Tracking**: Sentry
* **Analytics**: PostHog
* **Platform**: Vercel

## Non-Negotiables

* Correlation IDs must exist end-to-end (request → job → webhook)
* Alerts must exist for critical failures (webhook failures, auth attacks, drift)

## Context

Observability is about answering questions when things go wrong. It's 3am, something is broken, users are complaining — can you figure out what happened? How fast?

Good observability makes debugging easy. Bad observability means you're guessing, adding log lines, redeploying, and hoping. Consider: what questions would you need to answer during an incident, and can you answer them today?

## Driving Questions

* If something breaks in production right now, how would we find out?
* What blind spots exist where errors go unnoticed?
* How long would it take to trace a user's request through the entire system?
* What alerts exist, and do they fire for the right things?
* Where do we have noise that's training people to ignore alerts?
* What production issue in the last month was hard to debug, and why?