domains / families / software-engineering / error-diagnostics-smart-debug

error-diagnostics-smart-debug

combined

Diagnose software failures using observability data, ranked hypotheses, and targeted instrumentation. Use when the cause is unclear or an issue requires systematic investigation. Diagnose failures from reproduction steps, traces, logs and code; test hypotheses and verify a scoped fix without inventing production evidence.

When to use

• Working on error diagnostics smart debug tasks or workflows
• Needing guidance, best practices, or checklists for error diagnostics smart debug
• A reproducible failure or intermittent incident needs evidence-driven debugging.
• Existing telemetry must be compared with source and deployment changes before patching.

When not to use

• The task is unrelated to error diagnostics smart debug
• You need a different domain or tool outside this scope
• No supporting scripts or references are bundled in this entrypoint. Tool availability and real trace results must be checked in the current environment.
• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

Skill page

Conflict

Both copies describe the same 10-step debugging workflow, but they disagree on how to run triage, how to score hypotheses, and how to handle production chaos/instrumentation. The first copy mandates a debugger subagent, uses numeric probability scores, and lists Chaos Engineering as a strategy. The second copy requires user authorization for delegation, uses qualitative confidence, and restricts fault injection to isolated environments. Crowning one copy would hide these real operational differences.