Skill UI

This comprehensive guide teaches the best practices for writing effective, blameless postmortem reports following technical incidents. It provides a structured approach to documenting timelines, conducting root cause analysis (RCA), identifying systemic failures, and creating actionable follow-up items. Mastering this skill is crucial for fostering organizational learning and preventing future service disruptions.

A comprehensive guide for structured incident response when a Supabase-backed application fails. This runbook guides users through triaging issues, verifying platform status, inspecting connection pools, debugging stuck queries using pg_stat_activity, and analyzing Edge Function logs. Essential for root cause analysis and escalating issues to support.

This expert skill specializes in guiding comprehensive GitHub issue resolution. It covers systematic bug investigation, feature implementation, and collaborative development workflows. Expertise includes issue triage, root cause analysis, test-driven development, and professional pull request management, ensuring vague reports are transformed into production-ready code following modern CI/CD practices.

A comprehensive guide for diagnosing and resolving common Vercel deployment errors across build, runtime, and edge network layers. Use this resource when encountering failed deployments, 500/504 errors, or issues with serverless functions. It provides detailed root cause analysis and step-by-step fixes using CLI commands and log inspection.

A comprehensive, step-by-step guide for responding to Vercel-related production outages, deployment failures, and platform issues. This runbook covers rapid triage using CLI commands, executing instant rollbacks, investigating root causes (log analysis, diffing), managing communication templates, and conducting thorough postmortem reviews.

This skill enables AI-assisted debugging and comprehensive error analysis within the development environment. It utilizes Cascade to analyze complex error messages, stack traces, and surrounding code context to identify root causes. Use it when troubleshooting code or encountering runtime errors to receive detailed fix recommendations and prevention strategies.

A comprehensive runbook for handling critical incidents related to Windsurf AI features, service outages, or production bugs caused by generated code. It guides teams through triage, mitigation (including Git reverting), root cause analysis, and post-incident reporting to ensure rapid recovery and process improvement.

A forensic tool for performing post-mortem analysis on AI-assisted coding sessions. It goes beyond simply stating what was done, determining *why* work deviated (e.g., spec ambiguity, repo friction, agent error), identifying scope creep, and classifying rework patterns. It provides evidence-backed recommendations to improve prompts, codebase health, and future development workflows.

This skill provides a comprehensive, structured workflow for diagnosing performance bottlenecks in SwiftUI applications. It guides users through a code-first review to detect common issues like invalidation storms, layout thrash, or heavy main-thread work. When code review is insufficient, it provides detailed guidance on collecting runtime evidence using Instruments, enabling precise root cause analysis and targeted remediation strategies.

This skill teaches users to apply the scientific method to software debugging. Instead of random changes, it guides the process through five steps: Observation, Hypothesizing, Prediction, Testing, and Analysis. By systematically forming and testing specific, measurable hypotheses, users can efficiently isolate failing components and confirm the true root cause of technical issues.

Performs a systematic and structured investigation to determine the true source of bugs, errors, and unexpected system behavior, rather than merely treating symptoms. This method utilizes techniques like the Five Whys, hypothesis-driven testing, stack trace analysis, and gathering evidence (logs, git diffs) across multiple phases. It is ideal for complex, intermittent, or deeply rooted technical issues in software development.

A structured methodology for coordinating multiple, simultaneous investigation threads to determine the root cause of complex system failures, performance regressions, or integration bugs. This skill decomposes a large problem into independent tracks (e.g., database, application code, infrastructure), assigns ownership, and manages structured sync points (Continue/Pivot/Converge) to converge on a solution faster than serial debugging. Essential for high-stakes production incident response.