Atomizer/docs/plans/ATOMIZER_STUDY_INTERVIEW_MODE_IMPLEMENTATION_PLAN_TODO.md

Study Interview Mode - Implementation TODO

Created: 2026-01-02 Source: ATOMIZER_STUDY_INTERVIEW_MODE_IMPLEMENTATION_PLAN.md Status: COMPLETE - All Tasks Done

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Overview

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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3.5 Interview Intelligence

Status: [x] COMPLETE

Implemented in interview_intelligence.py:

• Complexity determination (simple/moderate/complex)
• Question estimation
• Recommended settings generation

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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

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4.2 BlueprintBuilder

Status: [x] COMPLETE

Implemented in study_blueprint.py:

• from_interview_state() method
• Automatic extractor assignment
• Trial count calculation
• Sampler selection

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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

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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

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5.2 Protocol Updates

Status: [x] COMPLETE

Completed:

• Update OP_01_CREATE_STUDY.md with interview phase
• Update 00_BOOTSTRAP.md task routing
• Update CLAUDE.md with interview instructions

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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)

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6.2 Integration Tests

Status: [x] COMPLETE

Integration tests in test_study_interview.py:

• Full interview flow
• Resume functionality
• Blueprint generation
• Warning handling

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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:

• All 129 tests passing
• All protocol updates complete
• Skill file created

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Quick Start

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()