TacoSkill LABTacoSkill LAB

The full-lifecycle AI skills platform.

Product

  • SkillHub
  • Playground
  • Skill Create
  • SkillKit

Resources

  • Privacy
  • Terms
  • About

Platforms

  • Claude Code
  • Cursor
  • Codex CLI
  • Gemini CLI
  • OpenCode

© 2026 TacoSkill LAB. All rights reserved.

TacoSkill LAB
TacoSkill LAB
HomeSkillHubCreatePlaygroundSkillKit
  1. Home
  2. /
  3. SkillHub
  4. /
  5. application-metrics
Improve

application-metrics

5.5

by majiayu000

133Favorites
79Upvotes
0Downvotes

Guide for instrumenting applications with metrics. Use when adding

metrics

5.5

Rating

0

Installs

DevOps & Infrastructure

Category

Quick Review

This skill provides a well-structured guide for instrumenting applications with metrics across common components (APIs, databases, queues, caching, locks). The description clearly indicates when to use it, and the content covers the five key metric types with naming conventions, component-specific checklists, and anti-patterns. Structure is clean with tables and organized sections. Task knowledge is solid for implementation - a CLI agent could follow the checklists and patterns to add instrumentation. Novelty is moderate: while the skill consolidates best practices that would otherwise require research and multiple tokens, the patterns themselves are relatively standard in the observability domain. The skill would save a CLI agent effort in researching metrics naming and coverage, but doesn't involve highly complex or proprietary logic.

LLM Signals

Description coverage8
Task knowledge8
Structure8
Novelty6

GitHub Signals

49
7
1
1
Last commit 0 days ago

Publisher

majiayu000

majiayu000

Skill Author

Related Skills

monitoring-expertcloud-architectsre-engineer

Loading SKILL.md…

Try onlineView on GitHub

Publisher

majiayu000 avatar
majiayu000

Skill Author

Related Skills

monitoring-expert

Jeffallan

6.4

cloud-architect

Jeffallan

5.8

sre-engineer

Jeffallan

6.4

terraform-engineer

Jeffallan

6.4
Try online