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SylphxAI

observability

by SylphxAI

🚀 AI development platform with MEP architecture - stop writing prompts, start building with 90% less typing

⭐ 4🍎 3📅 2026幎1月8日
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SKILL.md


name: observability description: Observability - logging, metrics, tracing. Use when adding monitoring.

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?

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総合スコア

75/100

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