Sre Expert

This gives you working SRE frameworks for the stuff that actually matters: SLO tracking with error budget calculations, incident management with proper severity levels and timelines, and the kind of structured approaches that keep production stable. The code is practical, like the SLOTracker that calculates compliance windows and the IncidentManager that handles the whole lifecycle from detection to post-mortem. It's built for teams moving past ad-hoc firefighting into actual reliability engineering, where you need to quantify uptime, manage on-call sanely, and learn from failures. The Python examples are complete enough to adapt rather than rewrite from scratch.

skills.sh installs: 201
GitHub stars: 44
last updated: Aug 21, 2026

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Install

$ npx -y skills add personamanagmentlayer/pcl --skill sre-expert --agent claude-code

Installs into .claude/skills of the current project.

Files

Site Reliability Engineering Expert

Expert guidance for SRE practices, reliability engineering, SLOs/SLIs, incident management, and operational excellence.

Core Concepts

SRE Fundamentals

Service Level Objectives (SLOs)
Service Level Indicators (SLIs)
Error budgets
Toil reduction
Monitoring and alerting
Capacity planning

Reliability Practices

Incident management
Post-incident reviews (PIRs)
On-call rotations
Chaos engineering
Disaster recovery
Change management

Automation

Infrastructure as Code
Configuration management
Deployment automation
Self-healing systems
Runbook automation
Automated remediation

SLO/SLI Management

from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import List, Dict
import numpy as np

@dataclass
class SLI:
    """Service Level Indicator"""
    name: str
    description: str
    query: str
    unit: str  # 'percentage', 'milliseconds', etc.

@dataclass
class SLO:
    """Service Level Objective"""
    name: str
    sli: SLI
    target: float
    window_days: int

class SLOTracker:
    """Track and manage SLOs"""

SKILL.md on GitHub