Trace Skill

Use this skill for ambiguous, causal, evidence-heavy questions where the goal is to explain why an observed result happened, not to jump directly into fixing or rewriting code.

This is the orchestration layer on top of the built-in tracer agent. The goal is to make tracing feel like a reusable OMC operating lane: restate the observation, generate competing explanations, gather evidence in parallel, rank the explanations, and propose the next probe that would collapse uncertainty fastest.

Good entry cases

Use /oh-my-claudecode:trace when the problem is:

• ambiguous
• causal
• evidence-heavy
• best answered by exploring competing explanations in parallel

Examples:

• runtime bugs and regressions
• performance / latency / resource behavior
• architecture / premortem / postmortem analysis
• scientific or experimental result tracing
• config / routing / orchestration behavior explanation
• “given this output, trace back the likely causes”

Core tracing contract

Always preserve these distinctions:

1. Observation -- what was actually observed
2. Hypotheses -- competing explanations
3. Evidence For -- what supports each explanation
4. Evidence Against / Gaps -- what contradicts it or is still missing
5. Current Best Explanation -- the leading explanation right now
6. Critical Unknown -- the missing fact keeping the top explanations apart
7. Discriminating Probe -- the highest-value next step to collapse uncertainty

Do not collapse into:

• a generic fix-it coding loop
• a generic debugger summary
• a raw dump of worker output
• fake certainty when evidence is incomplete

Evidence strength hierarchy

Treat evidence as ranked, not flat.

From strongest to weakest: