Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
Systematic debugging approach for ANY codebase, ANY language, ANY bug type
Observability patterns for metrics, logging, distributed tracing, and error tracking. Trigger: When setting up monitoring, when implementing logging, when adding error tracking, when configuring distributed tracing, when building health checks, when creating dashboards.
Patterns for debugging and understanding the root cause of code problems
Local-first codebase search with semantic understanding and multi-hop code discovery. Use for architecture analysis, dependency mapping, code research, and finding patterns across unfamiliar codebases. Triggers include "how does X work", "find pattern", "trace dependencies", "code archaeology", "architecture analysis".
Optimize application performance including build times, runtime speed, bundle size and resource usage. Use when addressing performance issues, implementing caching strategies, or optimizing rendering.
Guide for instrumenting applications with metrics. Use when adding observability, monitoring, metrics, counters, gauges, or instrumentation to code. Covers API endpoints, databases, queues, caching, and locks.
Systematic debugging approach for ANY codebase, ANY language, ANY bug type
VaultCPA project coding standards, conventions, and best practices for Next.js, React, TypeScript, Express, and Prisma. Use when reviewing code, writing new features, or setting up development patterns.
Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.
Use when user needs complex error pattern analysis, distributed system debugging, error correlation, root cause discovery, or predictive error prevention across microservices.
Proactively investigates Go SSO codebase to understand authentication flows, trace gRPC request paths, analyze clean architecture patterns, and provide comprehensive backend code insights. Use when users ask about SSO implementation, service structure, database queries, or need to understand how authentication/authorization works.
Standardized, hypothesis-driven debug investigation workflow for unexpected behavior, regressions, incidents, flaky tests, or production issues. Use to plan instrumentation, reproduce with decisive signals, compare runs, and narrow root cause without assuming any vendor or infrastructure.
Comprehensive error handling, structured logging patterns, API error response standards, and debugging strategies for Cloudflare Workers applications.
Evaluates codebase architecture for patterns, anti-patterns, coupling, cohesion, scalability, and technical debt. Use when assessing system design, reviewing architecture decisions, identifying improvement areas, or preparing for major refactoring.
Four-phase debugging framework that ensures root cause investigation before attempting fixes. Never jump to solutions.
Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.
Implement logging, metrics, tracing, and alerting for production applications. Covers structured logging (Pino, Winston), metrics (Prometheus, DataDog, CloudWatch), distributed tracing (OpenTelemetry), and alert design. Use this skill when adding logging to services, setting up monitoring, creating alerts, debugging production issues, or designing SLIs/SLOs. Triggers on "logging", "monitoring", "alerting", "observability", "metrics", "tracing", "debug production", "correlation id", "structured logging", "dashboards", "SLI", "SLO".
Review component architecture for React 19 best practices including size, composition, Server/Client boundaries, and anti-patterns. Use when reviewing component design.
Advanced debugging with stack trace analysis, error pattern detection, and fix suggestions. Use when delivering quick diagnostic support for everyday issues.
