Atomizer/.claude/skills/modules/study-interview-mode.md

Study Interview Mode Skill

Purpose

This skill enables an intelligent interview-based approach to study creation. Instead of asking users to fill out complex configuration files, Claude guides them through a natural conversation to gather all necessary information for optimization study setup.

This is now the DEFAULT mode for all study creation.

Triggers (DEFAULT for Study Creation)

This skill is automatically invoked when the user says ANY of:

• "create a study", "new study", "set up study"
• "create a study for my bracket"
• "optimize this", "optimize my model"
• "I want to minimize mass", "I want to reduce weight"
• Any study creation request

Skip Interview (Manual Mode)

Only skip to manual mode when user explicitly requests:

• "skip interview", "quick setup", "manual config"
• Power users recreating known configurations

Interview Flow

Phase 1: Introspection

Before questions begin, automatically analyze the NX model:

from optimization_engine.interview import StudyInterviewEngine

engine = StudyInterviewEngine(study_path)

# Run introspection first (if model available)
introspection = {
    "expressions": [...],  # From part introspection
    "materials": [...],    # From simulation
    "load_cases": [...],   # From simulation
    "model_path": "...",
    "sim_path": "..."
}

session = engine.start_interview(study_name, introspection=introspection)

Phase 2: Problem Definition

Ask about the study's purpose and context:

• What are you trying to optimize?
• Describe your study in a few words

Phase 3: Objectives

Determine optimization goals:

• Primary goal (minimize mass, stress, displacement, etc.)
• Secondary objectives (if any)
• Multi-objective or single-objective?

The ExtractorMapper automatically assigns extractors:

• Mass → E4 (BDF Mass) or E5 (CAD Mass)
• Displacement → E1
• Stress → E3
• Frequency → E2
• Zernike → E8, E9, E10

Phase 4: Constraints

Define physical limits:

• Material-aware validation (checks against yield stress)
• Auto-suggests safety factors
• Detects anti-patterns (e.g., mass minimization without constraints)

Phase 5: Design Variables

Select parameters to vary:

• Dynamic options from introspection
• Auto-suggests bounds based on current values
• Detects too-wide or too-narrow bounds

Phase 6: Validation

Final checks before generation:

• Run baseline simulation (optional)
• Verify all parameters accessible
• Check for conflicting constraints

Phase 7: Review

Present StudyBlueprint for confirmation:

• Show all settings in readable format
• Allow what-if modifications
• Confirm or restart

Key Classes

StudyInterviewEngine

Main orchestrator:

from optimization_engine.interview import StudyInterviewEngine

engine = StudyInterviewEngine(study_path)
session = engine.start_interview(study_name, introspection=introspection)

# Get first question
action = engine.get_first_question()
# Present action.message to user

# Process user answer
next_action = engine.process_answer(user_response)

# When complete, get blueprint
if next_action.action_type == "show_summary":
    blueprint = next_action.blueprint

InterviewState

Persisted interview state with JSON serialization:

from optimization_engine.interview import InterviewState, InterviewStateManager

manager = InterviewStateManager(study_path)
state = manager.load_state()  # Resume if exists

StudyBlueprint

Validated configuration ready for generation:

blueprint = engine.generate_blueprint()
config = blueprint.to_config_json()  # For optimization_config.json

Anti-Pattern Detection

The EngineeringValidator detects common mistakes:

• mass_no_constraint: Mass minimization without stress/displacement limits
• stress_over_yield: Stress constraint exceeds material yield
• bounds_too_wide: Design variable range > 100x
• too_many_objectives: More than 3 objectives
• single_dv_many_trials: Many trials for single variable

When detected, user is warned and asked to acknowledge.

Materials Database

Built-in materials with properties:

• Aluminum alloys (6061-T6, 7075-T6)
• Steel grades (A36, 304 SS, 316 SS)
• Titanium (Ti-6Al-4V)
• Composites (CFRP, GFRP)
• Plastics (ABS, Nylon)

Fuzzy matching supports user input like "Al 6061", "aluminum", "6061-T6".

Presenter Modes

ClaudePresenter (Default)

Markdown-formatted for Claude conversation:

### Question 1 of ~12: Problem Definition

What are you trying to optimize?

1. Minimize mass/weight
2. Minimize maximum stress
3. Minimize displacement
4. Maximize natural frequency

DashboardPresenter

JSON events for React dashboard (future).

CLIPresenter

Plain text for command-line interface (future).

State Persistence

Interview state is saved after each answer:

studies/my_study/
├── .interview/
│   ├── state.json         # Current state
│   ├── state.lock         # Concurrency lock
│   ├── interview_log.md   # Audit trail
│   └── backups/           # State history
│       ├── state_20260102_103000.json
│       └── ...

Supports resume after session interruption.

Integration with Study Wizard

After interview completes:

from optimization_engine.study.wizard import StudyWizard

wizard = StudyWizard.from_interview(blueprint, study_path)
wizard.generate()

Example Conversation

Claude: Let me help you set up your optimization study. I'll ask a few questions to understand what you're trying to achieve.

Claude: ### Question 1 of ~12: Problem Definition What are you trying to optimize? (You can describe in your own words)

User: I want to make this bracket as light as possible

Claude: Got it - mass minimization. Let me check the material...

Claude: ### Question 2 of ~12: Constraints Your model uses Aluminum 6061-T6 (yield stress: 276 MPa). What's the maximum allowable stress? I recommend staying below 184 MPa (SF=1.5).

User: 200 MPa should be fine

Claude: I notice 200 MPa is close to the yield stress. This allows minimal plastic deformation. Do you want to proceed with this value? [Yes/No]

User: Yes, proceed

(Interview continues...)

Claude: ### Summary Here's your optimization setup:

Setting	Value
Study Name	bracket_v1
Objective	Minimize mass (E4)
Constraint	Max stress ≤ 200 MPa
Design Variables	thickness [1-10 mm], rib_height [5-20 mm]
Trials	100
Sampler	TPE

Ready to generate? [Confirm/Modify/Restart]

Files Created

After confirmation, the following are generated:

• optimization_config.json - From blueprint.to_config_json()
• run_optimization.py - From SYS_10 or SYS_11 template
• INTERVIEW_LOG.md - Audit trail of Q&A

Error Handling

If the interview is interrupted:

1. State is auto-saved after each answer
2. On restart, detect existing state
3. Offer to resume or start fresh

If validation fails:

1. Present error with fix suggestion
2. Ask user to acknowledge or modify
3. Don't block on warnings, only on errors