# TECHNICAL REVIEW: Atomizer Project Standard Specification v1.0

**Reviewer:** Technical Lead (Subagent)  
**Date:** 2026-02-18  
**Specification Version:** 1.0 (Draft)  
**Review Scope:** Compatibility, feasibility, implementation complexity  

---

## Executive Summary

The proposed Atomizer Project Standard is **ambitious and well-designed** but requires **significant code changes** to be fully compatible with the existing optimization engine. The core concepts are sound, but several assumptions about auto-extraction and file organization need technical amendments.

**Overall Assessment:**
- ✅ **Philosophy**: Excellent — self-contained, LLM-native, rationale-first
- ⚠️ **AtomizerSpec v2.0 Integration**: Requires path refactoring in optimization engine
- ⚠️ **Auto-Extraction Claims**: Overstated — some extraction needs manual intervention
- ✅ **Study Lifecycle**: Good mapping to existing protocols, but gaps exist
- ⚠️ **Schema Alignment**: `.atomizer/project.json` creates redundancy
- ⚠️ **Model Organization**: Dual-location pattern is confusing
- ✅ **Report Generation**: Feasible with existing tooling
- ⚠️ **Playbooks**: Redundant with Protocol Operating System

**Recommendation:** Adopt with amendments. Priority order: Path compatibility → Auto-extraction → Schema consolidation → Documentation.

---

## 1. AtomizerSpec v2.0 Compatibility

### Current State

**File Paths in AtomizerSpec v2.0:**
```json
{
  "model": {
    "sim": {
      "path": "Model_sim1.sim"  // Relative to study root
    }
  }
}
```

**Optimization Engine Assumptions:**
```python
# optimization_engine/core/runner.py (line ~30)
self.config_path = Path(config_path)  # Expects config in study root or 1_setup/

# optimization_engine/nx/solver.py
# Expects model files in study_dir/1_setup/model/
```

**Current Study Structure:**
```
studies/{geometry_type}/{study_name}/
├── 1_setup/
│   ├── model/              # NX files here
│   └── atomizer_spec.json  # Config here (or optimization_config.json)
├── 2_iterations/
└── 3_results/
```

### Proposed Structure

```
{project-slug}/
├── 01-models/
│   ├── cad/Model.prt
│   ├── fem/Model_fem1.fem
│   └── sim/Model_sim1.sim
├── 03-studies/
│   └── {NN}_{slug}/
│       ├── atomizer_spec.json
│       └── 1_setup/
│           └── model/      # Study-specific model copy (if modified)
```

### Compatibility Issues

| Issue | Severity | Impact |
|-------|----------|--------|
| `atomizer_spec.json` path references assume study-relative paths | **HIGH** | Path resolution breaks if models are in `../../01-models/` |
| `OptimizationRunner.__init__()` expects config in study dir | **MEDIUM** | Need `--project-root` flag |
| Study archival assumes `1_setup/model/` is the source | **MEDIUM** | Backup/restore logic needs project-aware path |
| `TrialManager` trial numbering is study-scoped, not project-scoped | **LOW** | Multiple studies in a project can have overlapping trial numbers |

### Code Changes Required

#### Change 1: Add Project Root Awareness
**File:** `optimization_engine/core/runner.py`  
**Complexity:** Medium (2-4 hours)

```python
class OptimizationRunner:
    def __init__(
        self,
        config_path: Path,
        project_root: Optional[Path] = None,  # NEW
        model_updater: Callable,
        simulation_runner: Callable,
        result_extractors: Dict[str, Callable]
    ):
        self.config_path = Path(config_path)
        self.project_root = Path(project_root) if project_root else self.config_path.parent.parent  # NEW
        
        # Resolve model paths relative to project root
        if self.project_root:
            self.model_dir = self.project_root / "01-models"
        else:
            self.model_dir = self.config_path.parent / "1_setup" / "model"
```

**Priority:** P0 — Blocking for project-standard adoption

#### Change 2: Update AtomizerSpec Path Resolution
**File:** `optimization_engine/config/spec_models.py`  
**Complexity:** Low (1-2 hours)

Add `resolve_paths()` method to `AtomizerSpec`:

```python
class AtomizerSpec(BaseModel):
    # ... existing fields ...
    
    def resolve_paths(self, project_root: Path) -> None:
        """Resolve all relative paths against project root."""
        if self.model.sim.path:
            self.model.sim.path = str(project_root / "01-models" / "sim" / Path(self.model.sim.path).name)
        if self.model.fem and self.model.fem.path:
            self.model.fem.path = str(project_root / "01-models" / "fem" / Path(self.model.fem.path).name)
        # ... etc
```

**Priority:** P0 — Blocking

#### Change 3: Add `--project-root` CLI Flag
**File:** `run_optimization.py` (template)  
**Complexity:** Trivial (<1 hour)

```python
parser.add_argument(
    "--project-root",
    type=Path,
    default=None,
    help="Path to project root (for Atomizer Project Standard layout)"
)
```

**Priority:** P1 — Nice-to-have

### Recommendation

**Option A: Hybrid Mode (Recommended)**

Support BOTH layouts:
- **Legacy mode** (default): `studies/{study}/1_setup/model/`
- **Project mode**: `projects/{name}/03-studies/{study}/` + `--project-root` flag

Detect automatically:
```python
def detect_layout(study_dir: Path) -> str:
    if (study_dir.parent.parent / "01-models").exists():
        return "project-standard"
    return "legacy"
```

**Option B: Migration Tool**

Create `migrate_to_project_standard.py` that:
1. Creates `01-models/` and copies baseline model
2. Moves studies to `03-studies/{NN}_{slug}/`
3. Updates all `atomizer_spec.json` paths
4. Creates `.atomizer/project.json`

**Estimated Implementation:** 12-16 hours total

---

## 2. Study Lifecycle vs Real Workflow

### Proposed Lifecycle (Spec §6.1)

```
PLAN → CONFIGURE → VALIDATE → RUN → ANALYZE → REPORT → FEED-BACK
```

### Actual Atomizer Operations (Protocol Operating System)

| Operation | POS Protocol | Coverage in Spec |
|-----------|--------------|------------------|
| **OP_01: Create Study** | Bootstrap + study creation | ✅ PLAN + CONFIGURE |
| **OP_02: Run Optimization** | Execute trials | ✅ RUN |
| **OP_03: Monitor Progress** | Real-time tracking | ❌ Missing in lifecycle |
| **OP_04: Analyze Results** | Post-processing | ✅ ANALYZE |
| **OP_05: Export Training Data** | Neural acceleration | ❌ Missing |
| **OP_06: Troubleshoot** | Debug failures | ❌ Missing |
| **OP_07: Disk Optimization** | Free space | ❌ Missing |
| **OP_08: Generate Report** | Deliverables | ✅ REPORT |

### Gaps Identified

| Gap | Impact | Recommendation |
|-----|--------|----------------|
| No **MONITOR** stage | Real-time progress tracking is critical | Add between RUN and ANALYZE |
| No **EXPORT** stage | Neural surrogate training needs data | Add parallel to FEED-BACK |
| No **TROUBLESHOOT** stage | Optimization failures are common | Add decision tree in playbooks |
| No **DISK-OPTIMIZE** stage | `.op2` files fill disk quickly | Add to tools/ or playbooks |

### Recommended Lifecycle (Revised)

```
PLAN → CONFIGURE → VALIDATE → RUN → MONITOR → ANALYZE → REPORT → FEED-BACK
                                 ↓                              ↓
                              EXPORT (optional)           TROUBLESHOOT (if needed)
```

### Mapping to Spec Sections

| Lifecycle Stage | Spec Section | Protocol | Deliverable |
|-----------------|--------------|----------|-------------|
| PLAN | §6.2 Stage 1 | User-driven | `README.md` hypothesis |
| CONFIGURE | §6.2 Stage 2 | OP_01 | `atomizer_spec.json` |
| VALIDATE | §6.2 Stage 3 | OP_01 preflight | Validation report |
| RUN | §6.2 Stage 4 | OP_02 | `study.db`, `2_iterations/` |
| **MONITOR** | *Missing* | OP_03 | Real-time logs |
| ANALYZE | §6.2 Stage 5 | OP_04 | Plots, sensitivity |
| REPORT | §6.2 Stage 6 | OP_08 | `STUDY_REPORT.md` |
| FEED-BACK | §6.2 Stage 7 | Manual | KB updates |
| **EXPORT** | *Missing* | OP_05 | `training_data/` |
| **TROUBLESHOOT** | *Missing* | OP_06 | Fix + log |

**Estimated Amendment Effort:** 2-4 hours (documentation)

---

## 3. Auto-Extraction Feasibility

### Spec Claims (§7.2)

> "The Atomizer intake workflow already extracts:"

| Data | Claimed Source | Reality Check |
|------|---------------|---------------|
| All NX expressions | ✅ `introspect_part.py` | **VERIFIED** — works |
| Mass properties | ✅ NXOpen MeasureManager | **VERIFIED** — works |
| Material assignments | ❓ `.fem` material cards | **PARTIAL** — needs parser |
| Mesh statistics | ❓ `.fem` element/node counts | **PARTIAL** — needs parser |
| Boundary conditions | ❓ `.sim` constraint definitions | **NO** — not implemented |
| Load cases | ❓ `.sim` load definitions | **NO** — not implemented |
| Baseline solve results | ✅ `.op2` / `.f06` parsing | **VERIFIED** — pyNastran |
| Design variable candidates | ✅ Expression analysis | **VERIFIED** — confidence scoring exists |

### Actual Extraction Capabilities (E12 Introspector)

**File:** `optimization_engine/extractors/introspect_part.py`

**WORKS:**
```python
result = introspect_part("Model.prt")
# Returns:
{
    'expressions': {'user': [...], 'user_count': 47},
    'mass_properties': {'mass_kg': 1133.01, 'volume_mm3': ...},
    'materials': {'assigned': [...]},  # Material NAME only
    'bodies': {'solid_bodies': [...], 'counts': {...}},
    'features': {'total_count': 152, 'by_type': {...}},
}
```

**DOES NOT WORK:**
- **Material properties** (E, ν, ρ) — Requires `physicalmateriallibrary.xml` parsing (not implemented)
- **Boundary conditions** — `.sim` file is XML, no parser exists
- **Load cases** — Same issue
- **Mesh statistics** — `.fem` is BDF format, would need pyNastran `read_bdf()`

### Missing Extractors

| Missing Capability | File Format | Difficulty | Estimated Effort |
|--------------------|-------------|------------|------------------|
| Material property extraction | `.xml` | Low | 4-6 hours |
| Mesh statistics | `.fem` (BDF) | Low | 2-4 hours (use pyNastran) |
| BC extraction | `.sim` (XML) | Medium | 8-12 hours |
| Load extraction | `.sim` (XML) | Medium | 8-12 hours |

### Recommendations

#### Immediate Actions

1. **Update spec §7.2** to reflect reality:
   - ✅ Expression extraction: Fully automatic
   - ✅ Mass properties: Fully automatic
   - ⚠️ Material assignments: Name only (properties require manual entry or XML parser)
   - ⚠️ Mesh statistics: Requires BDF parser (pyNastran — 2 hours to implement)
   - ❌ Boundary conditions: Not automatic — manual KB entry or 8-12 hour XML parser
   - ❌ Load cases: Not automatic — manual KB entry

2. **Create roadmap** for missing extractors (§7.2 becomes aspirational):
   - Phase 1: Expression + Mass (DONE)
   - Phase 2: Mesh stats (2-4 hours)
   - Phase 3: Material properties (4-6 hours)
   - Phase 4: BCs + Loads (16-24 hours)

3. **Add to KB population protocol** (§7.3):
   - Auto-extraction runs what's available TODAY
   - User fills gaps via structured interview
   - KB entries flag: `source: auto|manual|mixed`

**Estimated Total Effort for Full Auto-Extraction:** 30-46 hours

---

## 4. Schema Alignment: `.atomizer/project.json` vs `atomizer_spec.json`

### Redundancy Analysis

**`.atomizer/project.json` (Spec §9.3):**
```json
{
  "project": {
    "slug": "thermoshield-bracket",
    "display_name": "ThermoShield Bracket",
    "created": "2026-02-15T...",
    "template_version": "1.0",
    "status": "active",
    "client": "SpaceCo",
    "model": {
      "cad_system": "NX",
      "solver": "NX_Nastran",
      "solution_type": "SOL101"
    },
    "studies_count": 3,
    "active_study": "03_cmaes_refinement",
    "tags": ["thermal", "satellite"]
  }
}
```

**`atomizer_spec.json` (per study):**
```json
{
  "meta": {
    "version": "2.0",
    "study_name": "03_cmaes_refinement",
    "created": "2026-02-16T...",
    "description": "...",
    "status": "running",
    "tags": ["thermal"]
  },
  "model": {
    "sim": {
      "path": "Model_sim1.sim",
      "solver": "nastran",
      "solution_type": "SOL101"
    }
  }
}
```

### Overlap Map

| Data | `.atomizer/project.json` | `atomizer_spec.json` | Redundant? |
|------|-------------------------|---------------------|------------|
| Project slug | ✅ | ❌ | No |
| Study name | ❌ | ✅ | No |
| Client | ✅ | ❌ | No |
| CAD system | ✅ | ✅ | **YES** |
| Solver | ✅ | ✅ | **YES** |
| Solution type | ✅ | ✅ | **YES** |
| Status | ✅ (project) | ✅ (study) | No (different scopes) |
| Tags | ✅ (project) | ✅ (study) | Partial (project vs study) |
| Created date | ✅ (project) | ✅ (study) | No (different events) |

### Issues

1. **Source of Truth Conflict:**
   - If `project.json` says `"solver": "nastran"` but a study spec says `"solver": "abaqus"`, which wins?
   - **Resolution:** Study spec ALWAYS wins (more specific). `project.json` is metadata only.

2. **Synchronization Burden:**
   - Creating a study requires updating BOTH files
   - Deleting a study requires updating `studies_count`, `active_study`
   - **Resolution:** Make `project.json` auto-generated (never hand-edit)

3. **Discoverability:**
   - `project.json` enables project-level queries ("show all NX projects")
   - But `atomizer_spec.json` metadata fields (`meta.tags`) already support this
   - **Resolution:** Keep project-level aggregation but make it derived

### Recommendation

**Option 1: Generate `project.json` on-demand (Recommended)**

```python
# optimization_engine/utils/project_manager.py (NEW)

def generate_project_json(project_root: Path) -> Dict[str, Any]:
    """Generate project.json from study specs + PROJECT.md frontmatter."""
    studies = list((project_root / "03-studies").glob("*/atomizer_spec.json"))
    
    # Aggregate from studies
    solvers = set()
    tags = set()
    for study_spec in studies:
        spec = AtomizerSpec.load(study_spec)
        solvers.add(spec.model.sim.solver)
        tags.update(spec.meta.tags or [])
    
    # Read PROJECT.md frontmatter for client, display_name
    frontmatter = parse_markdown_frontmatter(project_root / "PROJECT.md")
    
    return {
        "project": {
            "slug": project_root.name,
            "display_name": frontmatter.get("project", project_root.name),
            "client": frontmatter.get("client"),
            "created": frontmatter.get("created"),
            "template_version": frontmatter.get("template_version", "1.0"),
            "status": frontmatter.get("status", "active"),
            "model": {
                "solvers": list(solvers),  # List of solvers used across studies
            },
            "studies_count": len(studies),
            "tags": list(tags)
        }
    }
```

Call this on:
- Project creation (`atomizer project create`)
- Study creation/deletion
- Dashboard load

**Option 2: Eliminate `project.json` entirely**

Use `PROJECT.md` frontmatter as the source of truth for project metadata. Tools parse YAML frontmatter when needed.

**Pros:** No redundancy  
**Cons:** Slower parsing (MD vs JSON)

**Verdict:** Option 1. Keep `project.json` as a **cache**, auto-generated.

**Estimated Effort:** 4-6 hours

---

## 5. Model File Organization

### Proposed Dual-Location Pattern

**From Spec §2.1 and §10 (ThermoShield Bracket):**

```
thermoshield-bracket/
├── 01-models/                       # "Golden copies"
│   ├── cad/ThermoShield_Bracket.prt
│   ├── fem/ThermoShield_Bracket_fem1.fem
│   └── sim/ThermoShield_Bracket_sim1.sim
└── 03-studies/
    └── 03_cmaes_refinement/
        └── 1_setup/
            └── model/               # "Study-specific model copy (if modified)"
```

### Confusion Points

| Question | Current Atomizer | Spec Proposal | Issue |
|----------|------------------|---------------|-------|
| Where is the source model? | `1_setup/model/` | `01-models/` | Two locations |
| Where does the solver look? | `1_setup/model/` | Depends on study | Path confusion |
| When do I copy to study? | Always | "if modified" | Unclear trigger |
| What if study modifies model? | Study owns it | Study copy diverges | Sync problem |

### Real-World Example: Hydrotech Beam

**Current (works):**
```
projects/hydrotech-beam/
└── studies/
    └── 01_doe_landscape/
        └── 1_setup/
            └── model/
                ├── Beam.prt          # Study owns this
                ├── Beam_fem1.fem
                └── Beam_sim1.sim
```

**Proposed (spec):**
```
projects/hydrotech-beam/
├── 01-models/
│   ├── cad/Beam.prt                 # "Golden copy"
│   └── ...
└── 03-studies/
    └── 01_doe_landscape/
        └── 1_setup/
            └── model/               # Copy if modified? Or symlink?
```

**Problem:** Most optimization studies DO modify the model (that's the point). So "if modified" → "always".

### Alternative Interpretations

#### Interpretation A: `01-models/` is baseline, studies always copy

- `01-models/` = Baseline for comparison
- `03-studies/{NN}/1_setup/model/` = Working copy (always present)
- Pro: Clear separation
- Con: Disk waste (5+ studies × 500 MB models = 2.5 GB)

#### Interpretation B: `01-models/` is shared, studies symlink

- `01-models/` = Shared model files
- `03-studies/{NN}/1_setup/model/` = Symlinks to `../../../01-models/`
- Pro: No duplication
- Con: NX doesn't handle symlinks well on Windows

#### Interpretation C: Single source of truth (current Atomizer)

- `01-models/` = Documentation/reference only
- `03-studies/{NN}/1_setup/model/` = Actual working model
- Studies start from a baseline but own their model
- Pro: Simple, no sync issues
- Con: No "golden copy" for comparison

### Recommendation

**Adopt Interpretation C with amendments:**

1. **`01-models/baseline/`** contains:
   - Baseline `.prt`, `.fem`, `.sim`
   - `BASELINE.md` with documented metrics
   - `results/` with baseline `.op2`, `.f06`

2. **`03-studies/{NN}/1_setup/model/`** contains:
   - Working model for THIS study (copied from baseline at creation)
   - Study owns this and can modify

3. **Study creation workflow:**
   ```python
   def create_study(project_root, study_name):
       baseline = project_root / "01-models" / "baseline"
       study_model = project_root / "03-studies" / study_name / "1_setup" / "model"
       
       # Copy baseline to study
       shutil.copytree(baseline, study_model)
       
       # Study README notes: "Started from baseline (mass=X, disp=Y)"
   ```

4. **Update spec §5 (Model File Organization):**
   - Rename `01-models/` → `01-models/baseline/`
   - Clarify: "Studies copy from baseline at creation and own their model thereafter"
   - Add warning: "Do NOT modify `01-models/baseline/` during optimization"

**Estimated Effort:** 2 hours (documentation update)

---

## 6. Report Auto-Generation Feasibility

### Spec Claims (§8.2)

> "After a study completes, the following can be auto-generated from `study.db` + `iteration_history.csv` + `atomizer_spec.json`"

**Template:**
```markdown
# Study Report: {study_name}
## Configuration
{Auto-extracted from atomizer_spec.json}
## Results Summary
| Metric | Best | Mean | Worst | Target |
## Convergence
{Auto-generated convergence plot reference}
## Parameter Analysis
{Top parameter importances from Optuna}
## Best Trial Details
...
```

### Existing Capabilities

**File:** `optimization_engine/reporting/markdown_report.py`

```python
def generate_study_report(study_dir: Path, output_file: Path):
    """Generate markdown study report from Optuna database."""
    # ✅ Loads study.db
    # ✅ Extracts best trial, objectives, parameters
    # ✅ Generates convergence plot (matplotlib → PNG)
    # ✅ Computes parameter importance (Optuna fANOVA)
    # ✅ Writes markdown with tables
```

**Example Output (M1 Mirror V14):**
```markdown
# Study Report: m1_mirror_adaptive_V14

## Study Information
- **Algorithm**: TPE
- **Budget**: 785 trials
- **Objectives**: wfe_40_20_nm, wfe_60_20_nm, mfg_90_nm, mass_kg

## Best Trial (#743)
| Objective | Value |
|-----------|-------|
| wfe_40_20_nm | 5.99 |
| Weighted Sum | 121.72 |

## Parameter Importance
| Parameter | Importance |
|-----------|-----------|
| whiffle_min | 0.45 |
| lateral_inner_angle | 0.23 |
...
```

### Gaps vs Spec Template

| Spec Feature | Exists? | Gap |
|--------------|---------|-----|
| Configuration summary | ✅ | Works |
| Results summary table | ✅ | Works |
| Convergence plot | ✅ | Works |
| Parameter importance | ✅ | Works (Optuna fANOVA) |
| Feasibility breakdown | ❌ | Missing — need to parse trial states |
| Best trial geometry export | ❌ | Missing — need NX journal to export `.step` |
| Human annotation section | ✅ | Placeholder exists |

### Implementation Needs

#### Feature 1: Feasibility Breakdown

```python
def get_feasibility_stats(study: optuna.Study) -> Dict[str, int]:
    """Analyze trial feasibility."""
    stats = {
        'total': len(study.trials),
        'complete': 0,
        'failed': 0,
        'pruned': 0,
        'infeasible_geo': 0,      # Geometric constraint violation
        'infeasible_constraint': 0 # FEA constraint violation
    }
    for trial in study.trials:
        if trial.state == optuna.trial.TrialState.COMPLETE:
            stats['complete'] += 1
            # Check user_attrs for infeasibility reason
            if trial.user_attrs.get('infeasible_reason') == 'geometry':
                stats['infeasible_geo'] += 1
            elif trial.user_attrs.get('infeasible'):
                stats['infeasible_constraint'] += 1
        elif trial.state == optuna.trial.TrialState.FAIL:
            stats['failed'] += 1
    return stats
```

**Effort:** 2-4 hours

#### Feature 2: Best Trial Geometry Export

Requires NX journal to:
1. Load best trial model from `2_iterations/trial_{N}/`
2. Export as `.step` or `.x_t`
3. Save to `3_results/best_trial/geometry.step`

**Effort:** 4-6 hours (NX journal development)

### Recommendation

**Phase 1 (Immediate):** Use existing `markdown_report.py`, add:
- Feasibility stats (2-4 hours)
- Template for human annotation (already exists)

**Phase 2 (Future):** Add:
- Best trial geometry export (4-6 hours)
- Automated plot embedding in markdown (2 hours)

**Update Spec §8.2:** Note that geometry export is manual for now.

**Total Estimated Effort:** 8-12 hours for full auto-generation

---

## 7. Playbooks vs Protocol Operating System

### Spec Proposal (§2.1, §10)

```
playbooks/
├── FIRST_RUN.md              # How to run the first trial
└── MODAL_ANALYSIS.md         # How to extract frequency results
```

### Existing Protocol Operating System

```
docs/protocols/
├── operations/
│   ├── OP_01_CREATE_STUDY.md
│   ├── OP_02_RUN_OPTIMIZATION.md
│   ├── OP_03_MONITOR_PROGRESS.md
│   ├── OP_04_ANALYZE_RESULTS.md
│   └── ...
└── system/
    └── SYS_12_EXTRACTOR_LIBRARY.md
```

### Redundancy Analysis

| Playbook (Spec) | Protocol (Existing) | Overlap? |
|-----------------|---------------------|----------|
| `FIRST_RUN.md` | `OP_02_RUN_OPTIMIZATION.md` | **100%** — Same content |
| `MODAL_ANALYSIS.md` | `SYS_12_EXTRACTOR_LIBRARY.md` (E2: Frequency) | **90%** — Extractor docs cover this |
| `DOE_SETUP.md` (implied) | `OP_01_CREATE_STUDY.md` | **80%** — OP_01 includes sampler selection |

### Key Difference

**Protocols (POS):** Framework-level, generic, applies to all projects  
**Playbooks (Spec):** Project-specific, tailored to this exact component/study

**Example:**

**OP_02 (Protocol):**
```markdown
# OP_02: Run Optimization

## Quick Start
```bash
python run_optimization.py --start
```

## Monitoring
Check progress: `OP_03`
```

**FIRST_RUN.md (Playbook):**
```markdown
# First Run: ThermoShield Bracket

## Specific to THIS project
- Solver timeout: 600s (bracket solves fast)
- Watch for hole overlap infeasibility
- First 10 trials are DOE (LHS)

## Run
```bash
cd 03-studies/01_doe_landscape
python run_optimization.py --start
```

## Expected behavior
- Trial 1-10: ~30 seconds each (DOE)
- Trial 11+: TPE kicks in
- If mass > 0.8 kg → infeasible (auto-pruned)
```

### Recommendation

**Keep both, clarify distinction:**

1. **Playbooks** = Project-specific operational guides
   - Location: `{project}/playbooks/`
   - Content: Project quirks, expected behavior, troubleshooting for THIS project
   - Examples: "On this model, tip displacement is at node 5161"

2. **Protocols** = Generic framework operations
   - Location: `Atomizer/docs/protocols/`
   - Content: How Atomizer works in general
   - Examples: "To monitor, use OP_03"

3. **Update spec §2.1:**
   - Rename `playbooks/` → `playbooks/` (keep name)
   - Add description: "Project-specific operational notes. See `docs/protocols/` for generic Atomizer operations."

4. **Create template playbooks:**
   - `playbooks/FIRST_RUN.md` → Template with placeholders
   - `playbooks/TROUBLESHOOTING.md` → Project-specific issues log
   - `playbooks/EXTRACTOR_NOTES.md` → Custom extractor usage for this project

**Estimated Effort:** 2 hours (documentation)

---

## Summary of Recommendations

### Priority 0: Blocking Issues (Must Fix Before Adoption)

| Issue | Change | Effort | Owner |
|-------|--------|--------|-------|
| Path compatibility | Add project root awareness to `OptimizationRunner` | 2-4h | Dev |
| Path resolution | Update `AtomizerSpec.resolve_paths()` | 1-2h | Dev |
| Auto-extraction claims | Revise §7.2 to reflect reality | 1h | Manager |

**Total P0 Effort:** 4-7 hours

### Priority 1: Important Improvements

| Issue | Change | Effort | Owner |
|-------|--------|--------|-------|
| Study lifecycle gaps | Add MONITOR, EXPORT, TROUBLESHOOT stages | 2-4h | Manager |
| Model organization clarity | Amend §5 to clarify baseline vs working copy | 2h | Manager |
| Schema redundancy | Make `.atomizer/project.json` auto-generated | 4-6h | Dev |
| Report feasibility stats | Add feasibility breakdown to report generator | 2-4h | Dev |

**Total P1 Effort:** 10-16 hours

### Priority 2: Nice-to-Have

| Issue | Change | Effort | Owner |
|-------|--------|--------|-------|
| Full auto-extraction | Implement missing extractors (mesh, BC, loads) | 30-46h | Dev |
| Best trial geometry export | NX journal for `.step` export | 4-6h | Dev |
| Playbook templates | Create template playbooks | 2h | Manager |

**Total P2 Effort:** 36-54 hours

---

## Implementation Roadmap

### Phase 1: Core Compatibility (Week 1)
- [ ] Add project root awareness to optimization engine (4-7h)
- [ ] Update spec §7.2 auto-extraction claims (1h)
- [ ] Amend spec §6 lifecycle to include missing stages (2h)
- [ ] Clarify spec §5 model organization (2h)

**Deliverable:** Spec v1.1 (compatible with existing Atomizer)

### Phase 2: Enhanced Integration (Week 2-3)
- [ ] Implement `.atomizer/project.json` auto-generation (4-6h)
- [ ] Add feasibility stats to report generator (2-4h)
- [ ] Create playbook templates (2h)
- [ ] Test migration of Hydrotech Beam to project standard (4h)

**Deliverable:** Working project-standard template + migration tool

### Phase 3: Advanced Features (Future)
- [ ] Implement missing auto-extractors (30-46h)
- [ ] Best trial geometry export (4-6h)
- [ ] Dashboard integration for project view (TBD)

**Deliverable:** Full auto-population capability

---

## Technical Amendments to Specification

### Amendment 1: Section 1.2 Decision D3

**Current:**
> "Impact on Atomizer code: The optimization engine needs a `--project-root` flag or config entry pointing to the project folder."

**Amend to:**
> "Impact on Atomizer code:  
> 1. Add `project_root` parameter to `OptimizationRunner.__init__()`  
> 2. Update `AtomizerSpec.resolve_paths()` to handle `../../01-models/` references  
> 3. Add `--project-root` CLI flag to `run_optimization.py` template  
> 4. Maintain backward compatibility with legacy `studies/{name}/1_setup/model/` layout  
> **Estimated implementation:** 4-7 hours."

### Amendment 2: Section 5 (Model File Organization)

**Add new subsection §5.4: Model Location Decision Tree**

```markdown
### 5.4 Model Location Decision Tree

**Q: Where should I put the model files?**

| Scenario | Location | Rationale |
|----------|----------|-----------|
| Single study, no baseline comparison | `03-studies/01_study/1_setup/model/` | Simple, no duplication |
| Multiple studies from same baseline | `01-models/baseline/` + copy to studies | Baseline preserved for comparison |
| Studies modify model parametrically | `03-studies/{NN}/1_setup/model/` (copy) | Each study owns its model |
| Studies share exact same model | `01-models/` + symlink (advanced) | Disk savings — NX compatibility risk |

**Default recommendation:** Copy baseline to each study at creation.
```

### Amendment 3: Section 7.2 (Auto-Extraction Feasibility)

**Replace current table with:**

| Data | Auto-Extraction Status | Manual Fallback |
|------|----------------------|-----------------|
| All NX expressions | ✅ **Fully automatic** (`introspect_part.py`) | N/A |
| Mass properties | ✅ **Fully automatic** (NXOpen MeasureManager) | N/A |
| Material names | ✅ **Fully automatic** (part introspection) | N/A |
| Material properties (E, ν, ρ) | ⚠️ **Partial** — requires `physicalmateriallibrary.xml` parser (4-6h dev) | Manual entry in `02-kb/design/materials/{Material}.md` |
| Mesh statistics (element/node count) | ⚠️ **Requires implementation** — pyNastran BDF parser (2-4h dev) | Manual entry from NX Pre/Post |
| Boundary conditions | ❌ **Not implemented** — requires `.sim` XML parser (8-12h dev) | Manual documentation in `02-kb/analysis/boundary-conditions/` |
| Load cases | ❌ **Not implemented** — requires `.sim` XML parser (8-12h dev) | Manual documentation in `02-kb/analysis/loads/` |
| Baseline FEA results | ✅ **Fully automatic** (pyNastran `.op2` parsing) | N/A |
| Design variable candidates | ✅ **Fully automatic** (expression analysis + confidence scoring) | N/A |

**Total implementation effort for missing extractors:** 22-34 hours

### Amendment 4: Section 6.1 (Study Lifecycle)

**Replace §6.1 lifecycle diagram with:**

```
PLAN → CONFIGURE → VALIDATE → RUN → MONITOR → ANALYZE → REPORT → FEED-BACK
  │        │           │        │       │         │         │         │
  │        │           │        │       │         │         │         └─ Update KB (OP_LAC)
  │        │           │        │       │         │         └─ Generate STUDY_REPORT.md (OP_08)
  │        │           │        │       │         └─ Post-process, visualize (OP_04)
  │        │           │        │       └─ Real-time tracking (OP_03)
  │        │           │        └─ Execute trials (OP_02)
  │        │           └─ Preflight checks (OP_01)
  │        └─ Write atomizer_spec.json
  └─ Formulate hypothesis from previous study
  
  Optional branches:
  RUN ──→ EXPORT ──→ Train neural surrogate (OP_05)
  Any stage ──→ TROUBLESHOOT ──→ Fix + resume (OP_06)
```

### Amendment 5: Section 4.1 (DECISIONS.md vs .atomizer/project.json)

**Add clarification:**

> **Note on `.atomizer/project.json`:**  
> This file is **auto-generated** from study specs and `PROJECT.md` frontmatter. Do NOT hand-edit. If you need to update project metadata, edit `PROJECT.md` frontmatter and regenerate via:
> ```bash
> atomizer project refresh-metadata
> ```

---

## Compatibility Assessment Matrix

| Component | Works As-Is | Needs Code | Needs Doc | Priority |
|-----------|------------|-----------|-----------|----------|
| Numbered folders (`00-context/`, `01-models/`) | ✅ | ❌ | ❌ | - |
| `PROJECT.md` / `AGENT.md` entry points | ✅ | ❌ | ❌ | - |
| `DECISIONS.md` format | ✅ | ❌ | ❌ | - |
| `02-kb/` structure | ✅ | ❌ | ⚠️ Minor | P1 |
| `03-studies/{NN}_{slug}/` naming | ✅ | ❌ | ❌ | - |
| `atomizer_spec.json` in studies | ✅ | ⚠️ Path resolution | ❌ | **P0** |
| `01-models/` model source | ❌ | ✅ Path refactor | ✅ Clarify | **P0** |
| Auto-extraction claims | ❌ | ⚠️ Optional | ✅ Revise | **P0** |
| `.atomizer/project.json` | ❌ | ✅ Auto-gen | ✅ Note | P1 |
| `playbooks/` vs protocols | ⚠️ Overlap | ❌ | ✅ Clarify | P2 |
| Study lifecycle stages | ⚠️ Gaps | ❌ | ✅ Amend | P1 |
| `STUDY_REPORT.md` auto-gen | ⚠️ Partial | ⚠️ Feasibility stats | ❌ | P1 |

**Legend:**
- ✅ Good to go
- ⚠️ Needs attention
- ❌ Blocking issue

---

## Final Verdict

**The Atomizer Project Standard v1.0 is APPROVED with amendments.**

**Technical Feasibility:** ✅ High — Core concepts are sound  
**Implementation Complexity:** ⚠️ Medium — Requires 4-7 hours of core changes + 10-16 hours of improvements  
**Backward Compatibility:** ✅ Maintainable — Can support both legacy and project-standard layouts  
**Documentation Quality:** ✅ Excellent — Well-researched and thorough  
**Auto-Extraction Claims:** ⚠️ Overstated — Revise to reflect current capabilities  

**Recommended Action:**
1. Apply P0 amendments (path compatibility, auto-extraction reality check) → **Spec v1.1**
2. Implement P0 code changes (4-7 hours)
3. Test with Hydrotech Beam migration
4. Release project-standard template
5. Plan P1/P2 features for future sprints

**Risk Assessment:**
- **Low Risk:** Entry point design (`PROJECT.md`, `AGENT.md`), KB structure, naming conventions
- **Medium Risk:** Path refactoring (backward compat required), schema redundancy (sync issues)
- **High Risk:** Auto-extraction promises (user disappointment if not delivered)

**Mitigation:** Adopt hybrid mode (support both layouts), phase auto-extraction, clear documentation of what's automatic vs manual.

---

*End of Technical Review*

**Next Steps:** Deliver to Manager for CEO review integration.