Skill UI

This guide provides comprehensive details on the OpenPitrix application management system within KubeSphere. It covers the entire application lifecycle, including managing app repositories (Repo), uploading and versioning templates (Application/ApplicationVersion), conducting review processes, and finally deploying/upgrading applications (ApplicationRelease). Use this skill when troubleshooting App Store interactions, understanding KubeSphere's backend APIs, or managing deployed workloads.

This comprehensive workflow analyzes the health status of various AWS resources (EC2, Lambda, RDS, DynamoDB, etc.). It uses AWS CLI to diagnose potential issues by analyzing CloudWatch logs, metrics, and performance data. The process culminates in classifying root causes and generating actionable, tiered remediation plans (Immediate, Short-term, Long-term) to ensure system resilience and stability.

This skill provides a comprehensive governance audit for Fabric and Power BI tenant settings. It compares live configurations against a curated baseline to detect setting drift, analyze delegated overrides across capacities, domains, and workspaces, and investigate associated Entra security groups. It delivers authoritative, grounded, and actionable recommendations to ensure optimal enterprise governance.

A structured, multi-phase skill that systematically audits and provides actionable fixes for all four Lighthouse pillars: Performance, Accessibility, Best Practices, and SEO. It analyzes Core Web Vitals, render-blocking resources, security headers, and ARIA compliance to significantly boost site speed and quality.

This skill generates a formal Architecture Decision Record (ADR) following industry-standard formats. It guides users through documenting the full rationale behind significant technical choices, ensuring that the context, alternatives considered, chosen option, and resulting trade-offs are all captured. Ideal for maintaining architectural integrity and knowledge transfer within engineering teams.

This skill generates a comprehensive capacity plan document for any service. It assists technical teams in proactively managing infrastructure by modeling traffic growth, forecasting resource utilization (CPU, memory, connections), projecting costs, and defining clear scaling strategies. Use this when assessing current resource headroom, planning for seasonal peaks, or defining a long-term infrastructure action roadmap.

Generates a comprehensive, structured, and blameless incident postmortem document. This skill is designed for Root Cause Analysis (RCA), P1/P2 incident reviews, and outage reports, ensuring the focus remains on systemic gaps and preventative action items rather than individual blame. It guides the user through gathering all necessary details, from the timeline and impact to defining concrete action owners and due dates.

This guide helps define a complete observability stack for any service. It systematically covers the Four Golden Signals (latency, traffic, errors, saturation), guiding users to define core metrics, set Service Level Objectives (SLOs), configure actionable alerting rules, and structure comprehensive monitoring dashboards. Essential for establishing robust SRE practices and documenting system health standards.

This skill generates comprehensive, step-by-step operational runbooks for services, incidents, and deployments. It structures guides for on-call engineers, providing clear overviews, prerequisites, precise commands, rollback steps, troubleshooting tables, and escalation paths, ensuring continuity under pressure.

Generates comprehensive, structured documentation for microservices or internal platforms. This skill covers service identity, architecture context, APIs, SLAs, data classification, and operational runbooks, making it ideal for developer portals, service READMEs, and internal service registries. It ensures new team members can quickly understand how to use and depend on a shared service.

This skill guides the creation of a comprehensive Service Level Objective (SLO) document. It helps define Service Level Indicators (SLIs) by identifying critical user journeys and measuring key metrics like success rate and latency. It calculates the allowed "error budget" and establishes a burn rate policy to maintain service reliability while enabling feature velocity and principled trade-offs.