A technical utility for calculating SLO/SLA error budgets, allowed downtime, burn rates, and uptime metrics using precision duration syntax.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install slo-calculator
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install slo-calculator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The SLO Calculator is a specialized tool designed for Site Reliability Engineering (SRE) and DevOps workflows within the Openclaw Skills ecosystem. It enables engineers to translate abstract availability targets, such as the "four nines," into concrete downtime budgets across various time horizons like days, weeks, and months.
By providing clear visibility into error budgets and burn rates, this skill helps teams make data-driven decisions about feature velocity versus system stability. It simplifies the complex math behind multi-window analysis and SLA compliance, ensuring that availability targets are both measurable and actionable.
To use this tool within your Openclaw Skills environment, ensure you have Python 3 installed and the script available in your path:
# Basic budget calculation for 99.9% uptime
python3 scripts/slo.py budget 99.9
# Generate a full reference table for the year
python3 scripts/slo.py table --period year
The skill processes inputs through a flexible duration syntax and outputs structured data.
| Feature | Supported Formats / Syntax |
|---|---|
| Duration Syntax | 30s, 5m, 2h, 1d, 2h30m, 1d12h, or raw seconds |
| SLO Aliases | 99, 99.9, 99.99, two-nines, three-nines, four-nines, five-nines |
| Output Formats | text, json, markdown |
| Analysis Windows | day, week, month, year |
Loading
A sophisticated deployment management skill for executing feature-flagged dark launches with automated performance monitoring and promotion gates.

A specialized tool for analyzing document corpora and designing optimal chunking strategies to enhance RAG pipeline performance.

A multi-agent adversarial decision council that uses a 5-state consensus hardening protocol to produce auditable, high-confidence governance decisions.

A robust Python-based utility for auditing JSON-exported Tailwind CSS configurations to ensure structural integrity and production readiness.

An AI-enhanced diagnostic tool that scans codebases to identify, categorize, and prioritize technical debt with actionable remediation plans.

A lightweight Python-based utility to audit webpack configurations for structural errors, deprecated plugins, and performance optimization gaps.








































