# Study Interview Mode - Implementation TODO

**Created**: 2026-01-02
**Source**: [ATOMIZER_STUDY_INTERVIEW_MODE_IMPLEMENTATION_PLAN.md](ATOMIZER_STUDY_INTERVIEW_MODE_IMPLEMENTATION_PLAN.md)
**Status**: COMPLETE - All Tasks Done

---

## Overview

This document tracks the Interview Mode implementation. **All core components have been implemented and tests pass (129/129).**

---

## Phase 1: Foundation - COMPLETE

### 1.1 Directory Structure Setup
**Status**: `[x]` COMPLETE

**Files Created**:
```
optimization_engine/interview/
├── __init__.py
├── study_interview.py
├── question_engine.py
├── interview_state.py
├── interview_presenter.py
├── interview_intelligence.py
├── engineering_validator.py
├── study_blueprint.py
└── schemas/
    ├── interview_questions.json
    ├── materials_database.json
    └── anti_patterns.json

tests/interview/
├── __init__.py
├── test_interview_state.py
├── test_question_engine.py
├── test_interview_presenter.py
├── test_engineering_validator.py
├── test_study_blueprint.py
└── test_study_interview.py
```

---

### 1.2 InterviewState Dataclass
**Status**: `[x]` COMPLETE

Implemented in `interview_state.py`:
- InterviewState dataclass with all fields
- JSON serialization (to_json(), from_json())
- InterviewPhase enum with transitions
- Helper methods: is_complete(), progress_percentage(), add_warning(), etc.
- AnsweredQuestion and LogEntry dataclasses

---

### 1.3 InterviewStateManager
**Status**: `[x]` COMPLETE

Implemented in `interview_state.py`:
- Directory creation (.interview/, .interview/backups/)
- Atomic save with backup rotation
- Lock file mechanism
- Log file appending (INTERVIEW_LOG.md)
- History tracking

---

## Phase 2: Question Engine - COMPLETE

### 2.1 Question Schema
**Status**: `[x]` COMPLETE

Created `schemas/interview_questions.json`:
- 17 questions across 7 categories
- Conditional logic definitions
- Dynamic option population support
- Engineering guidance per question

---

### 2.2 QuestionEngine
**Status**: `[x]` COMPLETE

Implemented in `question_engine.py`:
- Schema loading and parsing
- Conditional evaluation (and/or/not/equals/contains/introspection_has)
- Dynamic option population from introspection
- Answer validation
- Category ordering

---

### 2.3 Interview Presenters
**Status**: `[x]` COMPLETE

Implemented in `interview_presenter.py`:
- InterviewPresenter abstract base class
- ClaudePresenter (markdown formatting)
- DashboardPresenter (JSON events)
- CLIPresenter (plain text)
- Response parsing for all question types

---

## Phase 3: Intelligence Layer - COMPLETE

### 3.1 ExtractorMapper
**Status**: `[x]` COMPLETE

Implemented in `interview_intelligence.py`:
- GOAL_MAP for goal-to-extractor mapping
- Support for all extractors E1-E10
- Auto-assignment based on optimization goal

---

### 3.2 Materials Database
**Status**: `[x]` COMPLETE

Created `schemas/materials_database.json`:
- 12 common engineering materials
- Properties: yield stress, ultimate stress, density, modulus
- Safety factors by application
- Fuzzy name matching implemented

---

### 3.3 Anti-Pattern Detector
**Status**: `[x]` COMPLETE

Created `schemas/anti_patterns.json` and implemented in `engineering_validator.py`:
- 12 anti-pattern definitions
- Severity levels (error, warning, info)
- Fix suggestions
- Pattern detection logic

---

### 3.4 Engineering Validator
**Status**: `[x]` COMPLETE

Implemented in `engineering_validator.py`:
- MaterialsDatabase class with fuzzy matching
- AntiPatternDetector class
- EngineeringValidator combining both
- Constraint validation (stress, displacement, frequency)
- Bounds suggestion

---

### 3.5 Interview Intelligence
**Status**: `[x]` COMPLETE

Implemented in `interview_intelligence.py`:
- Complexity determination (simple/moderate/complex)
- Question estimation
- Recommended settings generation

---

## Phase 4: Blueprint & Generation - COMPLETE

### 4.1 StudyBlueprint
**Status**: `[x]` COMPLETE

Implemented in `study_blueprint.py`:
- DesignVariable, Objective, Constraint dataclasses
- StudyBlueprint with all configuration
- to_config_json() for optimization_config.json format
- to_markdown() for summary display
- Validation methods

---

### 4.2 BlueprintBuilder
**Status**: `[x]` COMPLETE

Implemented in `study_blueprint.py`:
- from_interview_state() method
- Automatic extractor assignment
- Trial count calculation
- Sampler selection

---

### 4.3 StudyInterviewEngine
**Status**: `[x]` COMPLETE

Implemented in `study_interview.py`:
- Main orchestrator class
- start_interview() with resume support
- get_first_question() / process_answer() flow
- Warning acknowledgment
- Blueprint generation and modification
- State persistence

---

## Phase 5: Integration - COMPLETE

### 5.1 Skill File
**Status**: `[x]` COMPLETE

Created `.claude/skills/modules/study-interview-mode.md`:
- Usage documentation
- Example conversation
- Integration guide

---

### 5.2 Protocol Updates
**Status**: `[x]` COMPLETE

Completed:
- [x] Update OP_01_CREATE_STUDY.md with interview phase
- [x] Update 00_BOOTSTRAP.md task routing
- [x] Update CLAUDE.md with interview instructions

---

## Phase 6: Testing - COMPLETE

### 6.1 Unit Tests
**Status**: `[x]` COMPLETE

All tests pass: **129/129**

Test files created:
- test_interview_state.py (23 tests)
- test_question_engine.py (20 tests)
- test_interview_presenter.py (16 tests)
- test_engineering_validator.py (32 tests)
- test_study_blueprint.py (22 tests)
- test_study_interview.py (16 tests)

---

### 6.2 Integration Tests
**Status**: `[x]` COMPLETE

Integration tests in test_study_interview.py:
- Full interview flow
- Resume functionality
- Blueprint generation
- Warning handling

---

## Summary

| Phase | Status | Completion |
|-------|--------|------------|
| 1. Foundation | COMPLETE | 100% |
| 2. Question Engine | COMPLETE | 100% |
| 3. Intelligence | COMPLETE | 100% |
| 4. Blueprint | COMPLETE | 100% |
| 5. Integration | COMPLETE | 100% |
| 6. Testing | COMPLETE | 100% |

**Overall**: 100% Complete

**All Tasks Done**:
- [x] All 129 tests passing
- [x] All protocol updates complete
- [x] Skill file created

---

## Quick Start

```python
from optimization_engine.interview import StudyInterviewEngine

# Create engine
engine = StudyInterviewEngine(study_path)

# Start interview
session = engine.start_interview("my_study", introspection=introspection_data)

# Get first question
action = engine.get_first_question()
print(action.message)

# Process answers in loop
while action.action_type == "ask_question":
    user_response = input()
    action = engine.process_answer(user_response)

# When complete
if action.action_type == "show_summary":
    blueprint = action.blueprint
    config = blueprint.to_config_json()
```
