moai-essentials-debug

MoAI Essentials Debug is a high-performance diagnostic skill designed for developers and DevOps engineers who require rapid root cause analysis in complex environments. It supports 23 programming languages including C/C++, Rust, Go, Java, Python, and TypeScript, offering deep integration with native debuggers like gdb, lldb, Delve, debugpy, and Chrome DevTools. The skill is engineered to handle the nuances of modern software stacks, ranging from memory-unsafe systems programming to high-level async/await patterns and concurrent applications. It excels at parsing stack traces, identifying common error patterns, and providing actionable fix suggestions.

• Integrated support for containerized environments (Docker/Kubernetes) including ephemeral container debugging and remote process attachment.

• Comprehensive distributed tracing capabilities utilizing OpenTelemetry, Jaeger, and Zipkin to track cross-service requests.

• Performance profiling and bottleneck identification via Prometheus metrics, AWS X-Ray, and GCP Cloud Debugger.

• Systematic 6-step debugging workflow covering reproduction, isolation, hypothesis generation, experimentation, resolution, and verification.

• Language-specific memory safety tools including AddressSanitizer and Valgrind for low-level languages, and race detection for Go/Java.

• Automated trigger mechanisms invoked via debug-helper sub-agents during the Run stage to provide real-time diagnostic support.

• The skill is best used when encountering runtime exceptions, segmentation faults, concurrency data races, or unhandled promise rejections.

• Input requirements include access to source code, relevant stack traces, and environment configuration files.

• Users should provide specific error messages or behavior descriptions; the skill outputs prioritized diagnostic insights, refactoring advice, and CLI commands for immediate application.

• Operational constraints include the need for appropriate debugger ports to be accessible in containerized deployments and sufficient permissions for tool execution (e.g., kubectl, docker exec).