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deep-interview

Socratic deep interview with mathematical ambiguity gating. Activate when user says: deep interview, interview me, ask me everything, don't assume, make sure you understand, ouroboros, socratic, I have a vague idea, not sure exactly what I want.

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Dépôt
zereight/gitlab-mcp
Dernière activité de la source
12 avril 2026 à 05:11
Langue détectée de SKILL.md
anglais
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2 091
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368

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SKILL.md
Instructions source · Aperçu en lecture seule
name
deep-interview
description
Socratic deep interview with mathematical ambiguity gating. Activate when user says: deep interview, interview me, ask me everything, don't assume, make sure you understand, ouroboros, socratic, I have a vague idea, not sure exactly what I want.
argument-hint
[--quick|--standard|--deep] <idea or vague description>
# Deep Interview Ouroboros-inspired Socratic questioning with mathematical ambiguity scoring. Replaces vague ideas with crystal-clear specifications by asking targeted questions that expose hidden assumptions. ## Pipeline `deep-interview` → `ralplan` (consensus refinement) → `omg-autopilot` (execution) ## When to Use - User has a vague idea and wants thorough requirements gathering - Task is complex enough that jumping to code would waste cycles - User wants mathematically-validated clarity before execution ## When NOT to Use - Detailed specific request with file paths → execute directly - Quick fix → delegate to @executor or `/ralph` - User says "just do it" → respect their intent ## Phases ### Phase 1: Initialize 1. Parse the user's idea 2. Detect brownfield vs greenfield (use @explore to check codebase) 3. For brownfield: map relevant codebase areas 4. Initialize ambiguity score at 100% ### Phase 2: Interview Loop Repeat until ambiguity <= 20% or user exits early: 1. **Generate question** targeting the WEAKEST clarity dimension 2. **Ask ONE question at a time** with current ambiguity context 3. **Score ambiguity** across dimensions: - Goal Clarity (40% weight for greenfield, 35% brownfield) - Constraint Clarity (30% / 25%) - Success Criteria (30% / 25%) - Context Clarity (N/A / 15% for brownfield) 4. **Report progress** with dimension scores and gaps 5. **Track ontology** (key entities, stability ratio) ### Phase 3: Challenge Agents - Round 4+: **Contrarian** - challenge core assumptions - Round 6+: **Simplifier** - probe for complexity removal - Round 8+: **Ontologist** - find the essence (if ambiguity > 30%) ### Phase 4: Crystallize Spec When ambiguity <= threshold, generate spec to `.omc/specs/deep-interview-{slug}.md`: - Goal, Constraints, Non-Goals, Acceptance Criteria - Assumptions Exposed & Resolved - Ontology (Key Entities) with convergence tracking - Interview Transcript ### Phase 5: Execution Bridge Present options: 1. **Ralplan → OMG Autopilot** (Recommended): consensus-refine then execute 2. **Execute with omg-autopilot** (skip ralplan) 3. **Execute with ralph**: persistence loop 4. **Execute with team**: parallel agents 5. **Refine further**: continue interviewing ## Rules - Ask ONE question at a time - Target the WEAKEST clarity dimension each round - Gather codebase facts via @explore BEFORE asking user - Score ambiguity after every answer - Do not proceed until ambiguity <= threshold (default 20%) - Hard cap at 20 rounds, soft warning at 10
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