deep-interview

Deep Interview Skill

Socratic questioning to clarify requirements before execution.

Usage

/skill:deep-interview "I want to build something cool"
/skill:deep-interview "help me understand what we need"

Why This Exists

AI can build anything. The hard part is knowing WHAT to build.

Deep Interview ensures you have crystal-clear requirements before spending execution cycles.

Scoring Dimensions

Dimension	Weight	What it measures
Goal Clarity	40%	Can you state the objective in one sentence?
Constraint Clarity	30%	Are boundaries and limits clear?
Success Criteria	30%	Can we write tests that verify success?

Ambiguity Formula

ambiguity = 1 - (goal × 0.4 + constraints × 0.3 + criteria × 0.3)

Score	Meaning	Action
0-10%	Crystal clear	Proceed
10-20%	Clear enough	Proceed (default threshold)
20-40%	Some gaps	Continue questions
40-60%	Significant gaps	Focus on weakest
60-80%	Very unclear	May need reframing
80-100%	Almost nothing known	Early stages

Process

1. Initialize

{
  "active": true,
  "interview_id": "<uuid>",
  "initial_idea": "build something cool",
  "rounds": [],
  "current_ambiguity": 1.0,
  "threshold": 0.2
}

2. Ask One Question

Target the WEAKEST dimension:

Round 1 | Targeting: Goal Clarity | Ambiguity: 85%

"You mentioned wanting to build something cool. When you say this, 
what specific problem are you trying to solve? What does 'done' look like?"

3. Score After Answer

After Round 1:
- Goal Clarity: 0.4 (some understanding)
- Constraints: 0.2 (not discussed)
- Success Criteria: 0.1 (very vague)

Ambiguity: 1 - (0.4×0.4 + 0.2×0.3 + 0.1×0.3) = 73%

4. Report Progress

Round 1 complete.

| Dimension | Score | Weight | Weighted |
|-----------|-------|--------|----------|
| Goal | 0.4 | 0.4 | 0.16 |
| Constraints | 0.2 | 0.3 | 0.06 |
| Criteria | 0.1 | 0.3 | 0.03 |
| **Ambiguity** | | | **73%** |

Next target: Goal Clarity (lowest at 0.4)

5. Repeat Until ≤20%

• Ask one question per round
• Target weakest dimension
• Update scores
• Report progress

6. Generate Spec

When ambiguity ≤ threshold:

Create .omp/specs/deep-interview-{slug}.md:

# Deep Interview Spec: Task Management App

**Interview ID:** abc123
**Rounds:** 5
**Final Ambiguity:** 18%
**Generated:** 2024-01-15

## Goal
A task management REST API that allows users to create, organize, and track tasks with deadlines.

## Constraints
- Must use PostgreSQL
- REST API with JSON responses
- JWT authentication required
- Must handle 1000 concurrent users

## Success Criteria
- [ ] User can create tasks with title, description, due_date
- [ ] User can list their tasks, filter by status
- [ ] User can mark tasks complete
- [ ] User can set task deadlines and get reminders
- [ ] API responds in < 200ms for 95th percentile

## Questions Asked
1. "What problem are you solving?" → User needs to track work tasks
2. "What technology constraints?" → Must use existing PostgreSQL stack
3. "How do we know it's working?" → API tests, user acceptance testing

## Interview Transcript
[Full Q&A rounds]

7. Bridge to Execution

Interview complete! Ambiguity: 18% (threshold: 20%)

How would you like to proceed?
1. /skill:plan "implement this spec" (Recommended)
2. /skill:autopilot "build this spec"
3. /skill:ralph "implement this spec"
4. Continue interviewing

Question Templates

Goal Clarity

• "What exactly happens when...?"
• "Who is the user, and what do they need?"
• "What's the core problem, not the solution?"

Constraint Clarity

• "Are there technology constraints?"
• "What should this NOT do?"
• "Are there performance requirements?"

Success Criteria

• "How do we know it's working?"
• "What would make you say 'yes, that's it'?"
• "What tests would verify success?"

Challenge Questions (Round 4+)

Inject contrarian mode:

"You said this needs to support 10,000 users. What if it only 
needed 100? Would the architecture change?"

Inject simplifier mode:

"What's the simplest version that would still be valuable?"

Limits

• Soft limit: 10 rounds (warn user)
• Hard limit: 20 rounds (proceed with warning)
• Early exit: User can exit at any time with warning