mcpField
D
deep-dive

deep-dive

github.com/zereightAgent workflows2.1k58 installsUpdated today
Repository

About deep-dive

deep-dive is a skill for investigating an unclear problem before deciding how to address it. It runs parallel trace investigations, feeds findings into an interview, and bridges the resulting specification to execution options.

Key features

  1. 01Generate three investigation hypotheses
  2. 02Run parallel tracer lanes
  3. 03Compare evidence and unknowns
  4. 04Inject findings into an interview
  5. 05Save a specification with trace findings

Use cases

  1. 01Find the root cause of a bug
  2. 02Explore an improvement before defining requirements
  3. 03Turn an unclear problem into an execution-ready specification

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/zereight/gitlab-mcp --skill deep-dive

After installing, type/deep-divein Claude Code to confirm it loaded.

Details

From the project README

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.

Comments

Markdown supported