deep-dive

# Deep Dive Orchestrates a 2-stage pipeline: first investigate WHY something happened (trace), then define WHAT to do about it (deep-interview). Trace findings feed into the interview via 3-point injection. ## Pipeline `deep-dive` → `ralplan` (consensus refinement) → `omg-autopilot` (execution) ## When to Use - User has a problem but doesn't know the root cause - Bug investigation: "Something broke and I need to figure out why" - Feature exploration: "I want to improve X but first need to understand it" ## When NOT to Use - Already know the root cause → use `/deep-interview` - Clear specific request → execute directly - Investigation only, no requirements → use `/trace` ## Phases ### Phase 1: Initialize 1. Parse problem, detect brownfield/greenfield 2. Generate 3 trace lane hypotheses (code-path, config/env, measurement/artifact) ### Phase 2: Lane Confirmation Present hypotheses to user for confirmation (1 round). ### Phase 3: Trace Execution Run 3 parallel tracer lanes using @tracer agents: - Each lane: evidence for, evidence against, critical unknown, discriminating probe - Rebuttal round between top hypotheses - Convergence detection - Save to `.omc/specs/deep-dive-trace-{slug}.md` ### Phase 4: Interview with Trace Injection Follow deep-interview protocol with 3 overrides: 1. **initial_idea enrichment**: Include trace's most likely explanation 2. **codebase_context replacement**: Use trace synthesis (skip re-exploration) 3. **question queue injection**: Per-lane critical unknowns become first questions Low-confidence trace: don't inject uncertain conclusion, use ALL unknowns as questions. ### Phase 5: Execution Bridge Same options as deep-interview: ralplan → omg-autopilot (recommended), omg-autopilot, ralph, team, or refine further. ## Output Spec saved to `.omc/specs/deep-dive-{slug}.md` with additional "Trace Findings" section.