Skill UI

This skill enables parallel read-only multi-agent root-cause investigation for bugs, regressions, crashes, or unexplained failures. It deploys four specialized sub-agents to analyze reproduction, code paths, recent changes, and proof plans simultaneously. The main agent synthesizes findings into ranked hypotheses without editing files. Ideal for diagnosing complex software issues efficiently.

This comprehensive skill guides users through the entire debugging lifecycle, from reproducing elusive bugs to tracing the root cause, implementing permanent fixes, and preventing future regressions. It covers advanced techniques like binary search, time travel debugging, and handling common patterns such as race conditions and null values, ensuring professional and systematic troubleshooting for any production issue.

Four-phase debugging methodology with root cause analysis. Use when investigating bugs, fixing test failures, or troubleshooting unexpected behavior. Emphasizes NO FIXES WITHOUT ROOT CAUSE FIRST.

This skill provides a systematic framework for diagnosing and proposing structural repairs for organizational failures. It moves beyond personal blame by analyzing complex dynamics such as team structures, project bottlenecks, authority chains, and governance gaps. It generates actionable memos and low-risk pilot plans, ensuring solutions address systemic root causes rather than individual shortcomings. Best used when CrossFrame Suite routes explicit organizational tasks.

Expert debugging specialist for root cause analysis, error handling, test failure diagnosis, and unexpected behavior. Provides step-by-step guidance to isolate failures, implement minimal fixes, verify solutions, and prevent recurrence. Ideal for encountering any technical issues in development.

Interactively debug source code with the dap CLI: set breakpoints, step through execution line by line, inspect live variables and the call stack, evaluate expressions, and trace root causes across Python, Go, Node.js, Rust, and C/C++.

This skill provides a structured methodology for tackling complex bugs, performance bottlenecks, and production incidents. It guides users through reproducing issues, forming hypotheses, performing controlled experiments, and narrowing down the scope using proven strategies and tools. Ideal for deep dive troubleshooting and root cause analysis in complex software systems.

This skill offers expert guidance for AI-assisted debugging workflows and observability analysis. It covers root cause analysis, hypothesis generation, and production-safe debugging strategies using tools like Sentry and DataDog. Use it for troubleshooting errors, analyzing logs, and implementing validated fixes in development or production environments.

This skill specializes in debugging distributed systems and analyzing production incidents. It helps identify root causes of errors using observability tools, structured logging, and distributed tracing. You will implement fixes, establish preventive measures, and improve system reliability. Suitable for investigating recurring errors and designing error handling improvements.

Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across distributed systems, builds error timelines, and identifies root causes with actionable fixes and prevention strategies.

Systematic error analysis and resolution for debugging distributed systems, investigating production incidents, and implementing observability solutions. Provides root-cause analysis, structured logging, distributed tracing, and preventive measures to improve system reliability.

Expert AI-assisted debugging workflow for modern software systems. Covers triage, observability data collection, hypothesis generation, strategy selection, instrumentation, root cause analysis, fix implementation, validation, and prevention. Ideal for developers facing complex production issues.