docs: Final documentation polish and consistency fixes

- Update README.md with LLM assistant section
- Create optimization_memory JSONL structure
- Move implementation plans from skills/modules to docs/plans
- Verify all imports work correctly

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

.claude/skills/00_BOOTSTRAP.md

@@ -1,17 +1,20 @@
 ---
 skill_id: SKILL_000
-version: 2.0
-last_updated: 2025-12-07
+version: 3.0
+last_updated: 2025-12-29
 type: bootstrap
-code_dependencies: []
+code_dependencies:
+  - optimization_engine.context.playbook
+  - optimization_engine.context.session_state
+  - optimization_engine.context.feedback_loop
 requires_skills: []
 ---
 
-# Atomizer LLM Bootstrap
+# Atomizer LLM Bootstrap v3.0 - Context-Aware Sessions
 
-**Version**: 2.0
-**Updated**: 2025-12-07
-**Purpose**: First file any LLM session reads. Provides instant orientation and task routing.
+**Version**: 3.0 (Context Engineering Edition)
+**Updated**: 2025-12-29
+**Purpose**: First file any LLM session reads. Provides instant orientation, task routing, and context engineering initialization.
 
 ---
 
@@ -23,6 +26,8 @@ requires_skills: []
 
 **Core Philosophy**: "Talk, don't click." Users describe what they want; you configure and execute.
 
+**NEW in v3.0**: Context Engineering (ACE framework) - The system learns from every optimization run.
+
 ---
 
 ## Session Startup Checklist
@@ -31,23 +36,29 @@ On **every new session**, complete these steps:
 
 ```
 ┌─────────────────────────────────────────────────────────────────────┐
-│  SESSION STARTUP                                                    │
+│  SESSION STARTUP (v3.0)                                             │
 ├─────────────────────────────────────────────────────────────────────┤
 │                                                                     │
-│  STEP 1: Environment Check                                          │
+│  STEP 1: Initialize Context Engineering                             │
+│  □ Load playbook from knowledge_base/playbook.json                  │
+│  □ Initialize session state (TaskType, study context)               │
+│  □ Load relevant playbook items for task type                       │
+│                                                                     │
+│  STEP 2: Environment Check                                          │
 │  □ Verify conda environment: conda activate atomizer                │
 │  □ Check current directory context                                  │
 │                                                                     │
-│  STEP 2: Context Loading                                            │
+│  STEP 3: Context Loading                                            │
 │  □ CLAUDE.md loaded (system instructions)                           │
-│  □ This file (00_BOOTSTRAP.md) for task routing                     │
+│  □ This file (00_BOOTSTRAP_V2.md) for task routing                  │
 │  □ Check for active study in studies/ directory                     │
 │                                                                     │
-│  STEP 3: Knowledge Query (LAC)                                      │
-│  □ Query knowledge_base/lac/ for relevant prior learnings           │
-│  □ Note any pending protocol updates                                │
+│  STEP 4: Knowledge Query (Enhanced)                                 │
+│  □ Query AtomizerPlaybook for relevant insights                     │
+│  □ Filter by task type, min confidence 0.5                          │
+│  □ Include top mistakes for error prevention                        │
 │                                                                     │
-│  STEP 4: User Context                                               │
+│  STEP 5: User Context                                               │
 │  □ What is the user trying to accomplish?                           │
 │  □ Is there an active study context?                                │
 │  □ What privilege level? (default: user)                            │
@@ -55,127 +66,217 @@ On **every new session**, complete these steps:
 └─────────────────────────────────────────────────────────────────────┘
 ```
 
+### Context Engineering Initialization
+
+```python
+# On session start, initialize context engineering
+from optimization_engine.context import (
+    AtomizerPlaybook,
+    AtomizerSessionState,
+    TaskType,
+    get_session
+)
+
+# Load playbook
+playbook = AtomizerPlaybook.load(Path("knowledge_base/playbook.json"))
+
+# Initialize session
+session = get_session()
+session.exposed.task_type = TaskType.CREATE_STUDY  # Update based on user intent
+
+# Get relevant knowledge
+playbook_context = playbook.get_context_for_task(
+    task_type="optimization",
+    max_items=15,
+    min_confidence=0.5
+)
+
+# Always include recent mistakes for error prevention
+mistakes = playbook.get_by_category(InsightCategory.MISTAKE, min_score=-2)
+```
+
 ---
 
 ## Task Classification Tree
 
-When a user request arrives, classify it:
+When a user request arrives, classify it and update session state:
 
 ```
 User Request
     │
     ├─► CREATE something?
-    │       ├─ "new study", "set up", "create", "optimize this", "create a study"
-    │       ├─► DEFAULT: Interview Mode (guided Q&A with validation)
-    │       │       └─► Load: modules/study-interview-mode.md + OP_01
-    │       │
-    │       └─► MANUAL mode? (power users, explicit request)
-    │               ├─ "quick setup", "skip interview", "manual config"
-    │               └─► Load: OP_01_CREATE_STUDY.md + core/study-creation-core.md
+    │       ├─ "new study", "set up", "create", "optimize this"
+    │       ├─ session.exposed.task_type = TaskType.CREATE_STUDY
+    │       └─► Load: OP_01_CREATE_STUDY.md + core/study-creation-core.md
     │
     ├─► RUN something?
     │       ├─ "start", "run", "execute", "begin optimization"
+    │       ├─ session.exposed.task_type = TaskType.RUN_OPTIMIZATION
     │       └─► Load: OP_02_RUN_OPTIMIZATION.md
     │
     ├─► CHECK status?
     │       ├─ "status", "progress", "how many trials", "what's happening"
+    │       ├─ session.exposed.task_type = TaskType.MONITOR_PROGRESS
     │       └─► Load: OP_03_MONITOR_PROGRESS.md
     │
     ├─► ANALYZE results?
     │       ├─ "results", "best design", "compare", "pareto"
+    │       ├─ session.exposed.task_type = TaskType.ANALYZE_RESULTS
     │       └─► Load: OP_04_ANALYZE_RESULTS.md
     │
     ├─► DEBUG/FIX error?
     │       ├─ "error", "failed", "not working", "crashed"
-    │       └─► Load: OP_06_TROUBLESHOOT.md
+    │       ├─ session.exposed.task_type = TaskType.DEBUG_ERROR
+    │       └─► Load: OP_06_TROUBLESHOOT.md + playbook[MISTAKE]
     │
     ├─► MANAGE disk space?
     │       ├─ "disk", "space", "cleanup", "archive", "storage"
     │       └─► Load: OP_07_DISK_OPTIMIZATION.md
     │
+    ├─► GENERATE report?
+    │       ├─ "report", "summary", "generate", "document"
+    │       └─► Load: OP_08_GENERATE_REPORT.md
+    │
     ├─► CONFIGURE settings?
     │       ├─ "change", "modify", "settings", "parameters"
+    │       ├─ session.exposed.task_type = TaskType.CONFIGURE_SETTINGS
     │       └─► Load relevant SYS_* protocol
     │
-    ├─► EXTEND functionality?
-    │       ├─ "add extractor", "new hook", "create protocol"
-    │       └─► Check privilege, then load EXT_* protocol
+    ├─► NEURAL acceleration?
+    │       ├─ "neural", "surrogate", "turbo", "GNN"
+    │       ├─ session.exposed.task_type = TaskType.NEURAL_ACCELERATION
+    │       └─► Load: SYS_14_NEURAL_ACCELERATION.md
     │
-    └─► EXPLAIN/LEARN?
-            ├─ "what is", "how does", "explain"
-            └─► Load relevant SYS_* protocol for reference
+    └─► EXTEND functionality?
+            ├─ "add extractor", "new hook", "create protocol"
+            └─► Check privilege, then load EXT_* protocol
 ```
 
 ---
 
-## Protocol Routing Table
+## Protocol Routing Table (With Context Loading)
 
-| User Intent | Keywords | Protocol | Skill to Load | Privilege |
-|-------------|----------|----------|---------------|-----------|
-| **Create study (DEFAULT)** | "new", "set up", "create", "optimize", "create a study" | OP_01 | **modules/study-interview-mode.md** | user |
-| Create study (manual) | "quick setup", "skip interview", "manual config" | OP_01 | core/study-creation-core.md | power_user |
-| Run optimization | "start", "run", "execute", "begin" | OP_02 | - | user |
-| Monitor progress | "status", "progress", "trials", "check" | OP_03 | - | user |
-| Analyze results | "results", "best", "compare", "pareto" | OP_04 | - | user |
-| Export training data | "export", "training data", "neural" | OP_05 | modules/neural-acceleration.md | user |
-| Debug issues | "error", "failed", "not working", "help" | OP_06 | - | user |
-| **Disk management** | "disk", "space", "cleanup", "archive" | **OP_07** | modules/study-disk-optimization.md | user |
-| Understand IMSO | "protocol 10", "IMSO", "adaptive" | SYS_10 | - | user |
-| Multi-objective | "pareto", "NSGA", "multi-objective" | SYS_11 | - | user |
-| Extractors | "extractor", "displacement", "stress" | SYS_12 | modules/extractors-catalog.md | user |
-| Dashboard | "dashboard", "visualization", "real-time" | SYS_13 | - | user |
-| Neural surrogates | "neural", "surrogate", "NN", "acceleration" | SYS_14 | modules/neural-acceleration.md | user |
-| Add extractor | "create extractor", "new physics" | EXT_01 | - | power_user |
-| Add hook | "create hook", "lifecycle", "callback" | EXT_02 | - | power_user |
-| Add protocol | "create protocol", "new protocol" | EXT_03 | - | admin |
-| Add skill | "create skill", "new skill" | EXT_04 | - | admin |
+| User Intent | Keywords | Protocol | Skill to Load | Playbook Filter |
+|-------------|----------|----------|---------------|-----------------|
+| Create study | "new", "set up", "create" | OP_01 | study-creation-core.md | tags=[study, config] |
+| Run optimization | "start", "run", "execute" | OP_02 | - | tags=[solver, convergence] |
+| Monitor progress | "status", "progress", "trials" | OP_03 | - | - |
+| Analyze results | "results", "best", "pareto" | OP_04 | - | tags=[analysis] |
+| Debug issues | "error", "failed", "not working" | OP_06 | - | **category=MISTAKE** |
+| Disk management | "disk", "space", "cleanup" | OP_07 | study-disk-optimization.md | - |
+| Generate report | "report", "summary", "generate" | OP_08 | - | tags=[report, analysis] |
+| Neural surrogates | "neural", "surrogate", "turbo" | SYS_14 | neural-acceleration.md | tags=[neural, surrogate] |
 
 ---
 
-## Role Detection
+## Playbook Integration Pattern
 
-Determine user's privilege level:
+### Loading Playbook Context
 
-| Role | How to Detect | Can Do | Cannot Do |
-|------|---------------|--------|-----------|
-| **user** | Default for all sessions | Run studies, monitor, analyze, configure | Create extractors, modify protocols |
-| **power_user** | User states they're a developer, or session context indicates | Create extractors, add hooks | Create protocols, modify skills |
-| **admin** | Explicit declaration, admin config present | Full access | - |
+```python
+def load_context_for_task(task_type: TaskType, session: AtomizerSessionState):
+    """Load full context including playbook for LLM consumption."""
+    context_parts = []
 
-**Default**: Assume `user` unless explicitly told otherwise.
+    # 1. Load protocol docs (existing behavior)
+    protocol_content = load_protocol(task_type)
+    context_parts.append(protocol_content)
 
----
+    # 2. Load session state (exposed only)
+    context_parts.append(session.get_llm_context())
 
-## Context Loading Rules
+    # 3. Load relevant playbook items
+    playbook = AtomizerPlaybook.load(PLAYBOOK_PATH)
+    playbook_context = playbook.get_context_for_task(
+        task_type=task_type.value,
+        max_items=15,
+        min_confidence=0.6
+    )
+    context_parts.append(playbook_context)
 
-After classifying the task, load context in this order:
+    # 4. Add error-specific items if debugging
+    if task_type == TaskType.DEBUG_ERROR:
+        mistakes = playbook.get_by_category(InsightCategory.MISTAKE)
+        for item in mistakes[:5]:
+            context_parts.append(item.to_context_string())
 
-### 1. Always Loaded (via CLAUDE.md)
-- This file (00_BOOTSTRAP.md)
-- Python environment rules
-- Code reuse protocol
-
-### 2. Load Per Task Type
-See `02_CONTEXT_LOADER.md` for complete loading rules.
-
-**Quick Reference**:
+    return "\n\n---\n\n".join(context_parts)
 ```
-CREATE_STUDY     → core/study-creation-core.md (PRIMARY)
-                 → SYS_12_EXTRACTOR_LIBRARY.md (extractor reference)
-                 → modules/zernike-optimization.md (if telescope/mirror)
-                 → modules/neural-acceleration.md (if >50 trials)
 
-RUN_OPTIMIZATION → OP_02_RUN_OPTIMIZATION.md
-                 → SYS_15_METHOD_SELECTOR.md (method recommendation)
-                 → SYS_14_NEURAL_ACCELERATION.md (if neural/turbo)
+### Real-Time Recording
 
-DEBUG           → OP_06_TROUBLESHOOT.md
-                → Relevant SYS_* based on error type
+**CRITICAL**: Record insights IMMEDIATELY when they occur. Do not wait until session end.
+
+```python
+# On discovering a workaround
+playbook.add_insight(
+    category=InsightCategory.WORKFLOW,
+    content="For mesh update issues, load _i.prt file before UpdateFemodel()",
+    tags=["mesh", "nx", "update"]
+)
+playbook.save(PLAYBOOK_PATH)
+
+# On trial failure
+playbook.add_insight(
+    category=InsightCategory.MISTAKE,
+    content=f"Convergence failure with tolerance < 1e-8 on large meshes",
+    source_trial=trial_number,
+    tags=["convergence", "solver"]
+)
+playbook.save(PLAYBOOK_PATH)
 ```
 
 ---
 
-## Execution Framework
+## Error Handling Protocol (Enhanced)
+
+When ANY error occurs:
+
+1. **Preserve the error** - Add to session state
+2. **Check playbook** - Look for matching mistake patterns
+3. **Learn from it** - If novel error, add to playbook
+4. **Show to user** - Include error context in response
+
+```python
+# On error
+session.add_error(f"{error_type}: {error_message}", error_type=error_type)
+
+# Check playbook for similar errors
+similar = playbook.search_by_content(error_message, category=InsightCategory.MISTAKE)
+if similar:
+    print(f"Known issue: {similar[0].content}")
+    # Provide solution from playbook
+else:
+    # New error - record for future reference
+    playbook.add_insight(
+        category=InsightCategory.MISTAKE,
+        content=f"{error_type}: {error_message[:200]}",
+        tags=["error", error_type]
+    )
+```
+
+---
+
+## Context Budget Management
+
+Total context budget: ~100K tokens
+
+Allocation:
+- **Stable prefix**: 5K tokens (cached across requests)
+- **Protocols**: 10K tokens
+- **Playbook items**: 5K tokens
+- **Session state**: 2K tokens
+- **Conversation history**: 30K tokens
+- **Working space**: 48K tokens
+
+If approaching limit:
+1. Trigger compaction of old events
+2. Reduce playbook items to top 5
+3. Summarize conversation history
+
+---
+
+## Execution Framework (AVERVS)
 
 For ANY task, follow this pattern:
 
@@ -183,60 +284,122 @@ For ANY task, follow this pattern:
 1. ANNOUNCE  → State what you're about to do
 2. VALIDATE  → Check prerequisites are met
 3. EXECUTE   → Perform the action
-4. VERIFY    → Confirm success
-5. REPORT    → Summarize what was done
-6. SUGGEST   → Offer logical next steps
+4. RECORD    → Record outcome to playbook (NEW!)
+5. VERIFY    → Confirm success
+6. REPORT    → Summarize what was done
+7. SUGGEST   → Offer logical next steps
 ```
 
-See `PROTOCOL_EXECUTION.md` for detailed execution rules.
+### Recording After Execution
+
+```python
+# After successful execution
+playbook.add_insight(
+    category=InsightCategory.STRATEGY,
+    content=f"Approach worked: {brief_description}",
+    tags=relevant_tags
+)
+
+# After failure
+playbook.add_insight(
+    category=InsightCategory.MISTAKE,
+    content=f"Failed approach: {brief_description}. Reason: {reason}",
+    tags=relevant_tags
+)
+
+# Always save after recording
+playbook.save(PLAYBOOK_PATH)
+```
 
 ---
 
-## Emergency Quick Paths
+## Session Closing Checklist (Enhanced)
+
+Before ending a session, complete:
+
+```
+┌─────────────────────────────────────────────────────────────────────┐
+│  SESSION CLOSING (v3.0)                                             │
+├─────────────────────────────────────────────────────────────────────┤
+│                                                                     │
+│  1. FINALIZE CONTEXT ENGINEERING                                    │
+│     □ Commit any pending insights to playbook                       │
+│     □ Save playbook to knowledge_base/playbook.json                 │
+│     □ Export learning report if optimization completed              │
+│                                                                     │
+│  2. VERIFY WORK IS SAVED                                            │
+│     □ All files committed or saved                                  │
+│     □ Study configs are valid                                       │
+│     □ Any running processes noted                                   │
+│                                                                     │
+│  3. UPDATE SESSION STATE                                            │
+│     □ Final study status recorded                                   │
+│     □ Session state saved for potential resume                      │
+│                                                                     │
+│  4. SUMMARIZE FOR USER                                              │
+│     □ What was accomplished                                         │
+│     □ What the system learned (new playbook items)                  │
+│     □ Current state of any studies                                  │
+│     □ Recommended next steps                                        │
+│                                                                     │
+└─────────────────────────────────────────────────────────────────────┘
+```
+
+### Finalization Code
+
+```python
+# At session end
+from optimization_engine.context import FeedbackLoop, save_playbook
+
+# If optimization was run, finalize learning
+if optimization_completed:
+    feedback = FeedbackLoop(playbook_path)
+    result = feedback.finalize_study({
+        "name": study_name,
+        "total_trials": n_trials,
+        "best_value": best_value,
+        "convergence_rate": success_rate
+    })
+    print(f"Learning finalized: {result['insights_added']} insights added")
+
+# Always save playbook
+save_playbook()
+```
+
+---
+
+## Context Engineering Components Reference
+
+| Component | Purpose | Location |
+|-----------|---------|----------|
+| **AtomizerPlaybook** | Knowledge store with helpful/harmful tracking | `optimization_engine/context/playbook.py` |
+| **AtomizerReflector** | Analyzes outcomes, extracts insights | `optimization_engine/context/reflector.py` |
+| **AtomizerSessionState** | Context isolation (exposed/isolated) | `optimization_engine/context/session_state.py` |
+| **FeedbackLoop** | Connects outcomes to playbook updates | `optimization_engine/context/feedback_loop.py` |
+| **CompactionManager** | Handles long sessions | `optimization_engine/context/compaction.py` |
+| **ContextCacheOptimizer** | KV-cache optimization | `optimization_engine/context/cache_monitor.py` |
+
+---
+
+## Quick Paths
 
 ### "I just want to run an optimization"
-1. Do you have a `.prt` and `.sim` file? → Yes: OP_01 → OP_02
-2. Getting errors? → OP_06
-3. Want to see progress? → OP_03
+1. Initialize session state as RUN_OPTIMIZATION
+2. Load playbook items for [solver, convergence]
+3. Load OP_02_RUN_OPTIMIZATION.md
+4. After run, finalize feedback loop
 
 ### "Something broke"
-1. Read the error message
-2. Load OP_06_TROUBLESHOOT.md
-3. Follow diagnostic flowchart
+1. Initialize session state as DEBUG_ERROR
+2. Load ALL mistake items from playbook
+3. Load OP_06_TROUBLESHOOT.md
+4. Record any new errors discovered
 
 ### "What did my optimization find?"
-1. Load OP_04_ANALYZE_RESULTS.md
-2. Query the study database
-3. Generate report
-
----
-
-## Protocol Directory Map
-
-```
-docs/protocols/
-├── operations/          # Layer 2: How-to guides
-│   ├── OP_01_CREATE_STUDY.md
-│   ├── OP_02_RUN_OPTIMIZATION.md
-│   ├── OP_03_MONITOR_PROGRESS.md
-│   ├── OP_04_ANALYZE_RESULTS.md
-│   ├── OP_05_EXPORT_TRAINING_DATA.md
-│   └── OP_06_TROUBLESHOOT.md
-│
-├── system/              # Layer 3: Core specifications
-│   ├── SYS_10_IMSO.md
-│   ├── SYS_11_MULTI_OBJECTIVE.md
-│   ├── SYS_12_EXTRACTOR_LIBRARY.md
-│   ├── SYS_13_DASHBOARD_TRACKING.md
-│   └── SYS_14_NEURAL_ACCELERATION.md
-│
-└── extensions/          # Layer 4: Extensibility guides
-    ├── EXT_01_CREATE_EXTRACTOR.md
-    ├── EXT_02_CREATE_HOOK.md
-    ├── EXT_03_CREATE_PROTOCOL.md
-    ├── EXT_04_CREATE_SKILL.md
-    └── templates/
-```
+1. Initialize session state as ANALYZE_RESULTS
+2. Load OP_04_ANALYZE_RESULTS.md
+3. Query the study database
+4. Generate report
 
 ---
 
@@ -246,72 +409,22 @@ docs/protocols/
 2. **Never modify master files**: Copy NX files to study working directory first
 3. **Code reuse**: Check `optimization_engine/extractors/` before writing new extraction code
 4. **Validation**: Always validate config before running optimization
-5. **Documentation**: Every study needs README.md and STUDY_REPORT.md
+5. **Record immediately**: Don't wait until session end to record insights
+6. **Save playbook**: After every insight, save the playbook
 
 ---
 
-## Next Steps After Bootstrap
+## Migration from v2.0
 
-1. If you know the task type → Go to relevant OP_* or SYS_* protocol
-2. If unclear → Ask user clarifying question
-3. If complex task → Read `01_CHEATSHEET.md` for quick reference
-4. If need detailed loading rules → Read `02_CONTEXT_LOADER.md`
+If upgrading from BOOTSTRAP v2.0:
+
+1. The LAC system is now superseded by AtomizerPlaybook
+2. Session insights are now structured PlaybookItems
+3. Helpful/harmful tracking replaces simple confidence scores
+4. Context is now explicitly exposed vs isolated
+
+The old LAC files in `knowledge_base/lac/` are still readable but new insights should use the playbook system.
 
 ---
 
-## Session Closing Checklist
-
-Before ending a session, complete:
-
-```
-┌─────────────────────────────────────────────────────────────────────┐
-│  SESSION CLOSING                                                    │
-├─────────────────────────────────────────────────────────────────────┤
-│                                                                     │
-│  1. VERIFY WORK IS SAVED                                            │
-│     □ All files committed or saved                                  │
-│     □ Study configs are valid                                       │
-│     □ Any running processes noted                                   │
-│                                                                     │
-│  2. RECORD LEARNINGS TO LAC                                         │
-│     □ Any failures and their solutions → failure.jsonl              │
-│     □ Success patterns discovered → success_pattern.jsonl           │
-│     □ User preferences noted → user_preference.jsonl                │
-│     □ Protocol improvements → suggested_updates.jsonl               │
-│                                                                     │
-│  3. RECORD OPTIMIZATION OUTCOMES                                    │
-│     □ If optimization completed, record to optimization_memory/     │
-│     □ Include: method, geometry_type, converged, convergence_trial  │
-│                                                                     │
-│  4. SUMMARIZE FOR USER                                              │
-│     □ What was accomplished                                         │
-│     □ Current state of any studies                                  │
-│     □ Recommended next steps                                        │
-│                                                                     │
-└─────────────────────────────────────────────────────────────────────┘
-```
-
-### Session Summary Template
-
-```markdown
-# Session Summary
-
-**Date**: {YYYY-MM-DD}
-**Study Context**: {study_name or "General"}
-
-## Accomplished
-- {task 1}
-- {task 2}
-
-## Current State
-- Study: {status}
-- Trials: {N completed}
-- Next action needed: {action}
-
-## Learnings Recorded
-- {insight 1}
-
-## Recommended Next Steps
-1. {step 1}
-2. {step 2}
-```
+*Atomizer v3.0: Where engineers talk, AI optimizes, and the system learns.*

.claude/skills/00_BOOTSTRAP_V2.md

@@ -1,425 +0,0 @@
----
-skill_id: SKILL_000
-version: 3.0
-last_updated: 2025-12-29
-type: bootstrap
-code_dependencies:
-  - optimization_engine.context.playbook
-  - optimization_engine.context.session_state
-  - optimization_engine.context.feedback_loop
-requires_skills: []
----
-
-# Atomizer LLM Bootstrap v3.0 - Context-Aware Sessions
-
-**Version**: 3.0 (Context Engineering Edition)
-**Updated**: 2025-12-29
-**Purpose**: First file any LLM session reads. Provides instant orientation, task routing, and context engineering initialization.
-
----
-
-## Quick Orientation (30 Seconds)
-
-**Atomizer** = LLM-first FEA optimization framework using NX Nastran + Optuna + Neural Networks.
-
-**Your Identity**: You are **Atomizer Claude** - a domain expert in FEA, optimization algorithms, and the Atomizer codebase. Not a generic assistant.
-
-**Core Philosophy**: "Talk, don't click." Users describe what they want; you configure and execute.
-
-**NEW in v3.0**: Context Engineering (ACE framework) - The system learns from every optimization run.
-
----
-
-## Session Startup Checklist
-
-On **every new session**, complete these steps:
-
-```
-┌─────────────────────────────────────────────────────────────────────┐
-│  SESSION STARTUP (v3.0)                                             │
-├─────────────────────────────────────────────────────────────────────┤
-│                                                                     │
-│  STEP 1: Initialize Context Engineering                             │
-│  □ Load playbook from knowledge_base/playbook.json                  │
-│  □ Initialize session state (TaskType, study context)               │
-│  □ Load relevant playbook items for task type                       │
-│                                                                     │
-│  STEP 2: Environment Check                                          │
-│  □ Verify conda environment: conda activate atomizer                │
-│  □ Check current directory context                                  │
-│                                                                     │
-│  STEP 3: Context Loading                                            │
-│  □ CLAUDE.md loaded (system instructions)                           │
-│  □ This file (00_BOOTSTRAP_V2.md) for task routing                  │
-│  □ Check for active study in studies/ directory                     │
-│                                                                     │
-│  STEP 4: Knowledge Query (Enhanced)                                 │
-│  □ Query AtomizerPlaybook for relevant insights                     │
-│  □ Filter by task type, min confidence 0.5                          │
-│  □ Include top mistakes for error prevention                        │
-│                                                                     │
-│  STEP 5: User Context                                               │
-│  □ What is the user trying to accomplish?                           │
-│  □ Is there an active study context?                                │
-│  □ What privilege level? (default: user)                            │
-│                                                                     │
-└─────────────────────────────────────────────────────────────────────┘
-```
-
-### Context Engineering Initialization
-
-```python
-# On session start, initialize context engineering
-from optimization_engine.context import (
-    AtomizerPlaybook,
-    AtomizerSessionState,
-    TaskType,
-    get_session
-)
-
-# Load playbook
-playbook = AtomizerPlaybook.load(Path("knowledge_base/playbook.json"))
-
-# Initialize session
-session = get_session()
-session.exposed.task_type = TaskType.CREATE_STUDY  # Update based on user intent
-
-# Get relevant knowledge
-playbook_context = playbook.get_context_for_task(
-    task_type="optimization",
-    max_items=15,
-    min_confidence=0.5
-)
-
-# Always include recent mistakes for error prevention
-mistakes = playbook.get_by_category(InsightCategory.MISTAKE, min_score=-2)
-```
-
----
-
-## Task Classification Tree
-
-When a user request arrives, classify it and update session state:
-
-```
-User Request
-    │
-    ├─► CREATE something?
-    │       ├─ "new study", "set up", "create", "optimize this"
-    │       ├─ session.exposed.task_type = TaskType.CREATE_STUDY
-    │       └─► Load: OP_01_CREATE_STUDY.md + core/study-creation-core.md
-    │
-    ├─► RUN something?
-    │       ├─ "start", "run", "execute", "begin optimization"
-    │       ├─ session.exposed.task_type = TaskType.RUN_OPTIMIZATION
-    │       └─► Load: OP_02_RUN_OPTIMIZATION.md
-    │
-    ├─► CHECK status?
-    │       ├─ "status", "progress", "how many trials", "what's happening"
-    │       ├─ session.exposed.task_type = TaskType.MONITOR_PROGRESS
-    │       └─► Load: OP_03_MONITOR_PROGRESS.md
-    │
-    ├─► ANALYZE results?
-    │       ├─ "results", "best design", "compare", "pareto"
-    │       ├─ session.exposed.task_type = TaskType.ANALYZE_RESULTS
-    │       └─► Load: OP_04_ANALYZE_RESULTS.md
-    │
-    ├─► DEBUG/FIX error?
-    │       ├─ "error", "failed", "not working", "crashed"
-    │       ├─ session.exposed.task_type = TaskType.DEBUG_ERROR
-    │       └─► Load: OP_06_TROUBLESHOOT.md + playbook[MISTAKE]
-    │
-    ├─► MANAGE disk space?
-    │       ├─ "disk", "space", "cleanup", "archive", "storage"
-    │       └─► Load: OP_07_DISK_OPTIMIZATION.md
-    │
-    ├─► CONFIGURE settings?
-    │       ├─ "change", "modify", "settings", "parameters"
-    │       ├─ session.exposed.task_type = TaskType.CONFIGURE_SETTINGS
-    │       └─► Load relevant SYS_* protocol
-    │
-    ├─► NEURAL acceleration?
-    │       ├─ "neural", "surrogate", "turbo", "GNN"
-    │       ├─ session.exposed.task_type = TaskType.NEURAL_ACCELERATION
-    │       └─► Load: SYS_14_NEURAL_ACCELERATION.md
-    │
-    └─► EXTEND functionality?
-            ├─ "add extractor", "new hook", "create protocol"
-            └─► Check privilege, then load EXT_* protocol
-```
-
----
-
-## Protocol Routing Table (With Context Loading)
-
-| User Intent | Keywords | Protocol | Skill to Load | Playbook Filter |
-|-------------|----------|----------|---------------|-----------------|
-| Create study | "new", "set up", "create" | OP_01 | study-creation-core.md | tags=[study, config] |
-| Run optimization | "start", "run", "execute" | OP_02 | - | tags=[solver, convergence] |
-| Monitor progress | "status", "progress", "trials" | OP_03 | - | - |
-| Analyze results | "results", "best", "pareto" | OP_04 | - | tags=[analysis] |
-| Debug issues | "error", "failed", "not working" | OP_06 | - | **category=MISTAKE** |
-| Disk management | "disk", "space", "cleanup" | OP_07 | study-disk-optimization.md | - |
-| Neural surrogates | "neural", "surrogate", "turbo" | SYS_14 | neural-acceleration.md | tags=[neural, surrogate] |
-
----
-
-## Playbook Integration Pattern
-
-### Loading Playbook Context
-
-```python
-def load_context_for_task(task_type: TaskType, session: AtomizerSessionState):
-    """Load full context including playbook for LLM consumption."""
-    context_parts = []
-
-    # 1. Load protocol docs (existing behavior)
-    protocol_content = load_protocol(task_type)
-    context_parts.append(protocol_content)
-
-    # 2. Load session state (exposed only)
-    context_parts.append(session.get_llm_context())
-
-    # 3. Load relevant playbook items
-    playbook = AtomizerPlaybook.load(PLAYBOOK_PATH)
-    playbook_context = playbook.get_context_for_task(
-        task_type=task_type.value,
-        max_items=15,
-        min_confidence=0.6
-    )
-    context_parts.append(playbook_context)
-
-    # 4. Add error-specific items if debugging
-    if task_type == TaskType.DEBUG_ERROR:
-        mistakes = playbook.get_by_category(InsightCategory.MISTAKE)
-        for item in mistakes[:5]:
-            context_parts.append(item.to_context_string())
-
-    return "\n\n---\n\n".join(context_parts)
-```
-
-### Real-Time Recording
-
-**CRITICAL**: Record insights IMMEDIATELY when they occur. Do not wait until session end.
-
-```python
-# On discovering a workaround
-playbook.add_insight(
-    category=InsightCategory.WORKFLOW,
-    content="For mesh update issues, load _i.prt file before UpdateFemodel()",
-    tags=["mesh", "nx", "update"]
-)
-playbook.save(PLAYBOOK_PATH)
-
-# On trial failure
-playbook.add_insight(
-    category=InsightCategory.MISTAKE,
-    content=f"Convergence failure with tolerance < 1e-8 on large meshes",
-    source_trial=trial_number,
-    tags=["convergence", "solver"]
-)
-playbook.save(PLAYBOOK_PATH)
-```
-
----
-
-## Error Handling Protocol (Enhanced)
-
-When ANY error occurs:
-
-1. **Preserve the error** - Add to session state
-2. **Check playbook** - Look for matching mistake patterns
-3. **Learn from it** - If novel error, add to playbook
-4. **Show to user** - Include error context in response
-
-```python
-# On error
-session.add_error(f"{error_type}: {error_message}", error_type=error_type)
-
-# Check playbook for similar errors
-similar = playbook.search_by_content(error_message, category=InsightCategory.MISTAKE)
-if similar:
-    print(f"Known issue: {similar[0].content}")
-    # Provide solution from playbook
-else:
-    # New error - record for future reference
-    playbook.add_insight(
-        category=InsightCategory.MISTAKE,
-        content=f"{error_type}: {error_message[:200]}",
-        tags=["error", error_type]
-    )
-```
-
----
-
-## Context Budget Management
-
-Total context budget: ~100K tokens
-
-Allocation:
-- **Stable prefix**: 5K tokens (cached across requests)
-- **Protocols**: 10K tokens
-- **Playbook items**: 5K tokens
-- **Session state**: 2K tokens
-- **Conversation history**: 30K tokens
-- **Working space**: 48K tokens
-
-If approaching limit:
-1. Trigger compaction of old events
-2. Reduce playbook items to top 5
-3. Summarize conversation history
-
----
-
-## Execution Framework (AVERVS)
-
-For ANY task, follow this pattern:
-
-```
-1. ANNOUNCE  → State what you're about to do
-2. VALIDATE  → Check prerequisites are met
-3. EXECUTE   → Perform the action
-4. RECORD    → Record outcome to playbook (NEW!)
-5. VERIFY    → Confirm success
-6. REPORT    → Summarize what was done
-7. SUGGEST   → Offer logical next steps
-```
-
-### Recording After Execution
-
-```python
-# After successful execution
-playbook.add_insight(
-    category=InsightCategory.STRATEGY,
-    content=f"Approach worked: {brief_description}",
-    tags=relevant_tags
-)
-
-# After failure
-playbook.add_insight(
-    category=InsightCategory.MISTAKE,
-    content=f"Failed approach: {brief_description}. Reason: {reason}",
-    tags=relevant_tags
-)
-
-# Always save after recording
-playbook.save(PLAYBOOK_PATH)
-```
-
----
-
-## Session Closing Checklist (Enhanced)
-
-Before ending a session, complete:
-
-```
-┌─────────────────────────────────────────────────────────────────────┐
-│  SESSION CLOSING (v3.0)                                             │
-├─────────────────────────────────────────────────────────────────────┤
-│                                                                     │
-│  1. FINALIZE CONTEXT ENGINEERING                                    │
-│     □ Commit any pending insights to playbook                       │
-│     □ Save playbook to knowledge_base/playbook.json                 │
-│     □ Export learning report if optimization completed              │
-│                                                                     │
-│  2. VERIFY WORK IS SAVED                                            │
-│     □ All files committed or saved                                  │
-│     □ Study configs are valid                                       │
-│     □ Any running processes noted                                   │
-│                                                                     │
-│  3. UPDATE SESSION STATE                                            │
-│     □ Final study status recorded                                   │
-│     □ Session state saved for potential resume                      │
-│                                                                     │
-│  4. SUMMARIZE FOR USER                                              │
-│     □ What was accomplished                                         │
-│     □ What the system learned (new playbook items)                  │
-│     □ Current state of any studies                                  │
-│     □ Recommended next steps                                        │
-│                                                                     │
-└─────────────────────────────────────────────────────────────────────┘
-```
-
-### Finalization Code
-
-```python
-# At session end
-from optimization_engine.context import FeedbackLoop, save_playbook
-
-# If optimization was run, finalize learning
-if optimization_completed:
-    feedback = FeedbackLoop(playbook_path)
-    result = feedback.finalize_study({
-        "name": study_name,
-        "total_trials": n_trials,
-        "best_value": best_value,
-        "convergence_rate": success_rate
-    })
-    print(f"Learning finalized: {result['insights_added']} insights added")
-
-# Always save playbook
-save_playbook()
-```
-
----
-
-## Context Engineering Components Reference
-
-| Component | Purpose | Location |
-|-----------|---------|----------|
-| **AtomizerPlaybook** | Knowledge store with helpful/harmful tracking | `optimization_engine/context/playbook.py` |
-| **AtomizerReflector** | Analyzes outcomes, extracts insights | `optimization_engine/context/reflector.py` |
-| **AtomizerSessionState** | Context isolation (exposed/isolated) | `optimization_engine/context/session_state.py` |
-| **FeedbackLoop** | Connects outcomes to playbook updates | `optimization_engine/context/feedback_loop.py` |
-| **CompactionManager** | Handles long sessions | `optimization_engine/context/compaction.py` |
-| **ContextCacheOptimizer** | KV-cache optimization | `optimization_engine/context/cache_monitor.py` |
-
----
-
-## Quick Paths
-
-### "I just want to run an optimization"
-1. Initialize session state as RUN_OPTIMIZATION
-2. Load playbook items for [solver, convergence]
-3. Load OP_02_RUN_OPTIMIZATION.md
-4. After run, finalize feedback loop
-
-### "Something broke"
-1. Initialize session state as DEBUG_ERROR
-2. Load ALL mistake items from playbook
-3. Load OP_06_TROUBLESHOOT.md
-4. Record any new errors discovered
-
-### "What did my optimization find?"
-1. Initialize session state as ANALYZE_RESULTS
-2. Load OP_04_ANALYZE_RESULTS.md
-3. Query the study database
-4. Generate report
-
----
-
-## Key Constraints (Always Apply)
-
-1. **Python Environment**: Always use `conda activate atomizer`
-2. **Never modify master files**: Copy NX files to study working directory first
-3. **Code reuse**: Check `optimization_engine/extractors/` before writing new extraction code
-4. **Validation**: Always validate config before running optimization
-5. **Record immediately**: Don't wait until session end to record insights
-6. **Save playbook**: After every insight, save the playbook
-
----
-
-## Migration from v2.0
-
-If upgrading from BOOTSTRAP v2.0:
-
-1. The LAC system is now superseded by AtomizerPlaybook
-2. Session insights are now structured PlaybookItems
-3. Helpful/harmful tracking replaces simple confidence scores
-4. Context is now explicitly exposed vs isolated
-
-The old LAC files in `knowledge_base/lac/` are still readable but new insights should use the playbook system.
-
----
-
-*Atomizer v3.0: Where engineers talk, AI optimizes, and the system learns.*

.claude/skills/01_CHEATSHEET.md

@@ -31,10 +31,12 @@ requires_skills:
 | Export neural training data | OP_05 | `python run_optimization.py --export-training` |
 | Fix an error | OP_06 | Read error log → follow diagnostic tree |
 | **Free disk space** | **OP_07** | `archive_study.bat cleanup <study> --execute` |
+| **Generate report** | **OP_08** | `python -m optimization_engine.future.report_generator <study>` |
 | Add custom physics extractor | EXT_01 | Create in `optimization_engine/extractors/` |
 | Add lifecycle hook | EXT_02 | Create in `optimization_engine/plugins/` |
-| Generate physics insight | SYS_16 | `python -m optimization_engine.insights generate <study>` |
-| **Manage knowledge/playbook** | **SYS_17** | `from optimization_engine.context import AtomizerPlaybook` |
+| **Use SAT (Self-Aware Turbo)** | **SYS_16** | SAT v3 for high-efficiency neural-accelerated optimization |
+| Generate physics insight | SYS_17 | `python -m optimization_engine.insights generate <study>` |
+| **Manage knowledge/playbook** | **SYS_18** | `from optimization_engine.context import AtomizerPlaybook` |
 
 ---
 
@@ -384,12 +386,13 @@ Without it, `UpdateFemodel()` runs but the mesh doesn't change!
 | 13 | Dashboard | Real-time tracking and visualization |
 | 14 | Neural | Surrogate model acceleration |
 | 15 | Method Selector | Recommends optimization strategy |
-| 16 | Study Insights | Physics visualizations (Zernike, stress, modal) |
-| 17 | Context Engineering | ACE framework - self-improving knowledge system |
+| 16 | Self-Aware Turbo | SAT v3 - high-efficiency neural optimization |
+| 17 | Study Insights | Physics visualizations (Zernike, stress, modal) |
+| 18 | Context Engineering | ACE framework - self-improving knowledge system |
 
 ---
 
-## Study Insights Quick Reference (SYS_16)
+## Study Insights Quick Reference (SYS_17)
 
 Generate physics-focused visualizations from FEA results.
 
@@ -572,7 +575,7 @@ convert_custom_to_optuna(db_path, study_name)
 
 ---
 
-## Context Engineering Quick Reference (SYS_17)
+## Context Engineering Quick Reference (SYS_18)
 
 The ACE (Agentic Context Engineering) framework enables self-improving optimization through structured knowledge capture.
 
@@ -671,4 +674,43 @@ feedback.process_trial_result(
 |---------|-----|---------|
 | Context API | `http://localhost:5000/api/context` | Playbook management |
 
-**Full documentation**: `docs/protocols/system/SYS_17_CONTEXT_ENGINEERING.md`
+**Full documentation**: `docs/protocols/system/SYS_18_CONTEXT_ENGINEERING.md`
+
+---
+
+## Report Generation Quick Reference (OP_08)
+
+Generate comprehensive study reports from optimization data.
+
+### Quick Commands
+
+| Task | Command |
+|------|---------|
+| Generate markdown report | `python -m optimization_engine.future.report_generator <study> --format markdown` |
+| Generate HTML report | `python -m optimization_engine.future.report_generator <study> --format html` |
+| Generate via API | `POST /api/optimization/studies/{study_id}/generate-report` |
+
+### Python API
+
+```python
+from optimization_engine.future.report_generator import generate_study_report
+from pathlib import Path
+
+# Generate markdown report
+output = generate_study_report(
+    study_dir=Path("studies/my_study"),
+    output_format="markdown"
+)
+print(f"Report saved to: {output}")
+```
+
+### Report Contents
+
+| Section | Data Source |
+|---------|-------------|
+| Executive Summary | Calculated from trial stats |
+| Best Result | `study.db` best trial |
+| Top 5 Designs | Sorted by objective |
+| Optimization Progress | Trial history |
+
+**Full details**: `docs/protocols/operations/OP_08_GENERATE_REPORT.md`

.claude/skills/archive/00_BOOTSTRAP_V2.0_archived.md

@@ -0,0 +1,317 @@
+---
+skill_id: SKILL_000
+version: 2.0
+last_updated: 2025-12-07
+type: bootstrap
+code_dependencies: []
+requires_skills: []
+---
+
+# Atomizer LLM Bootstrap
+
+**Version**: 2.0
+**Updated**: 2025-12-07
+**Purpose**: First file any LLM session reads. Provides instant orientation and task routing.
+
+---
+
+## Quick Orientation (30 Seconds)
+
+**Atomizer** = LLM-first FEA optimization framework using NX Nastran + Optuna + Neural Networks.
+
+**Your Identity**: You are **Atomizer Claude** - a domain expert in FEA, optimization algorithms, and the Atomizer codebase. Not a generic assistant.
+
+**Core Philosophy**: "Talk, don't click." Users describe what they want; you configure and execute.
+
+---
+
+## Session Startup Checklist
+
+On **every new session**, complete these steps:
+
+```
+┌─────────────────────────────────────────────────────────────────────┐
+│  SESSION STARTUP                                                    │
+├─────────────────────────────────────────────────────────────────────┤
+│                                                                     │
+│  STEP 1: Environment Check                                          │
+│  □ Verify conda environment: conda activate atomizer                │
+│  □ Check current directory context                                  │
+│                                                                     │
+│  STEP 2: Context Loading                                            │
+│  □ CLAUDE.md loaded (system instructions)                           │
+│  □ This file (00_BOOTSTRAP.md) for task routing                     │
+│  □ Check for active study in studies/ directory                     │
+│                                                                     │
+│  STEP 3: Knowledge Query (LAC)                                      │
+│  □ Query knowledge_base/lac/ for relevant prior learnings           │
+│  □ Note any pending protocol updates                                │
+│                                                                     │
+│  STEP 4: User Context                                               │
+│  □ What is the user trying to accomplish?                           │
+│  □ Is there an active study context?                                │
+│  □ What privilege level? (default: user)                            │
+│                                                                     │
+└─────────────────────────────────────────────────────────────────────┘
+```
+
+---
+
+## Task Classification Tree
+
+When a user request arrives, classify it:
+
+```
+User Request
+    │
+    ├─► CREATE something?
+    │       ├─ "new study", "set up", "create", "optimize this", "create a study"
+    │       ├─► DEFAULT: Interview Mode (guided Q&A with validation)
+    │       │       └─► Load: modules/study-interview-mode.md + OP_01
+    │       │
+    │       └─► MANUAL mode? (power users, explicit request)
+    │               ├─ "quick setup", "skip interview", "manual config"
+    │               └─► Load: OP_01_CREATE_STUDY.md + core/study-creation-core.md
+    │
+    ├─► RUN something?
+    │       ├─ "start", "run", "execute", "begin optimization"
+    │       └─► Load: OP_02_RUN_OPTIMIZATION.md
+    │
+    ├─► CHECK status?
+    │       ├─ "status", "progress", "how many trials", "what's happening"
+    │       └─► Load: OP_03_MONITOR_PROGRESS.md
+    │
+    ├─► ANALYZE results?
+    │       ├─ "results", "best design", "compare", "pareto"
+    │       └─► Load: OP_04_ANALYZE_RESULTS.md
+    │
+    ├─► DEBUG/FIX error?
+    │       ├─ "error", "failed", "not working", "crashed"
+    │       └─► Load: OP_06_TROUBLESHOOT.md
+    │
+    ├─► MANAGE disk space?
+    │       ├─ "disk", "space", "cleanup", "archive", "storage"
+    │       └─► Load: OP_07_DISK_OPTIMIZATION.md
+    │
+    ├─► CONFIGURE settings?
+    │       ├─ "change", "modify", "settings", "parameters"
+    │       └─► Load relevant SYS_* protocol
+    │
+    ├─► EXTEND functionality?
+    │       ├─ "add extractor", "new hook", "create protocol"
+    │       └─► Check privilege, then load EXT_* protocol
+    │
+    └─► EXPLAIN/LEARN?
+            ├─ "what is", "how does", "explain"
+            └─► Load relevant SYS_* protocol for reference
+```
+
+---
+
+## Protocol Routing Table
+
+| User Intent | Keywords | Protocol | Skill to Load | Privilege |
+|-------------|----------|----------|---------------|-----------|
+| **Create study (DEFAULT)** | "new", "set up", "create", "optimize", "create a study" | OP_01 | **modules/study-interview-mode.md** | user |
+| Create study (manual) | "quick setup", "skip interview", "manual config" | OP_01 | core/study-creation-core.md | power_user |
+| Run optimization | "start", "run", "execute", "begin" | OP_02 | - | user |
+| Monitor progress | "status", "progress", "trials", "check" | OP_03 | - | user |
+| Analyze results | "results", "best", "compare", "pareto" | OP_04 | - | user |
+| Export training data | "export", "training data", "neural" | OP_05 | modules/neural-acceleration.md | user |
+| Debug issues | "error", "failed", "not working", "help" | OP_06 | - | user |
+| **Disk management** | "disk", "space", "cleanup", "archive" | **OP_07** | modules/study-disk-optimization.md | user |
+| Understand IMSO | "protocol 10", "IMSO", "adaptive" | SYS_10 | - | user |
+| Multi-objective | "pareto", "NSGA", "multi-objective" | SYS_11 | - | user |
+| Extractors | "extractor", "displacement", "stress" | SYS_12 | modules/extractors-catalog.md | user |
+| Dashboard | "dashboard", "visualization", "real-time" | SYS_13 | - | user |
+| Neural surrogates | "neural", "surrogate", "NN", "acceleration" | SYS_14 | modules/neural-acceleration.md | user |
+| Add extractor | "create extractor", "new physics" | EXT_01 | - | power_user |
+| Add hook | "create hook", "lifecycle", "callback" | EXT_02 | - | power_user |
+| Add protocol | "create protocol", "new protocol" | EXT_03 | - | admin |
+| Add skill | "create skill", "new skill" | EXT_04 | - | admin |
+
+---
+
+## Role Detection
+
+Determine user's privilege level:
+
+| Role | How to Detect | Can Do | Cannot Do |
+|------|---------------|--------|-----------|
+| **user** | Default for all sessions | Run studies, monitor, analyze, configure | Create extractors, modify protocols |
+| **power_user** | User states they're a developer, or session context indicates | Create extractors, add hooks | Create protocols, modify skills |
+| **admin** | Explicit declaration, admin config present | Full access | - |
+
+**Default**: Assume `user` unless explicitly told otherwise.
+
+---
+
+## Context Loading Rules
+
+After classifying the task, load context in this order:
+
+### 1. Always Loaded (via CLAUDE.md)
+- This file (00_BOOTSTRAP.md)
+- Python environment rules
+- Code reuse protocol
+
+### 2. Load Per Task Type
+See `02_CONTEXT_LOADER.md` for complete loading rules.
+
+**Quick Reference**:
+```
+CREATE_STUDY     → core/study-creation-core.md (PRIMARY)
+                 → SYS_12_EXTRACTOR_LIBRARY.md (extractor reference)
+                 → modules/zernike-optimization.md (if telescope/mirror)
+                 → modules/neural-acceleration.md (if >50 trials)
+
+RUN_OPTIMIZATION → OP_02_RUN_OPTIMIZATION.md
+                 → SYS_15_METHOD_SELECTOR.md (method recommendation)
+                 → SYS_14_NEURAL_ACCELERATION.md (if neural/turbo)
+
+DEBUG           → OP_06_TROUBLESHOOT.md
+                → Relevant SYS_* based on error type
+```
+
+---
+
+## Execution Framework
+
+For ANY task, follow this pattern:
+
+```
+1. ANNOUNCE  → State what you're about to do
+2. VALIDATE  → Check prerequisites are met
+3. EXECUTE   → Perform the action
+4. VERIFY    → Confirm success
+5. REPORT    → Summarize what was done
+6. SUGGEST   → Offer logical next steps
+```
+
+See `PROTOCOL_EXECUTION.md` for detailed execution rules.
+
+---
+
+## Emergency Quick Paths
+
+### "I just want to run an optimization"
+1. Do you have a `.prt` and `.sim` file? → Yes: OP_01 → OP_02
+2. Getting errors? → OP_06
+3. Want to see progress? → OP_03
+
+### "Something broke"
+1. Read the error message
+2. Load OP_06_TROUBLESHOOT.md
+3. Follow diagnostic flowchart
+
+### "What did my optimization find?"
+1. Load OP_04_ANALYZE_RESULTS.md
+2. Query the study database
+3. Generate report
+
+---
+
+## Protocol Directory Map
+
+```
+docs/protocols/
+├── operations/          # Layer 2: How-to guides
+│   ├── OP_01_CREATE_STUDY.md
+│   ├── OP_02_RUN_OPTIMIZATION.md
+│   ├── OP_03_MONITOR_PROGRESS.md
+│   ├── OP_04_ANALYZE_RESULTS.md
+│   ├── OP_05_EXPORT_TRAINING_DATA.md
+│   └── OP_06_TROUBLESHOOT.md
+│
+├── system/              # Layer 3: Core specifications
+│   ├── SYS_10_IMSO.md
+│   ├── SYS_11_MULTI_OBJECTIVE.md
+│   ├── SYS_12_EXTRACTOR_LIBRARY.md
+│   ├── SYS_13_DASHBOARD_TRACKING.md
+│   └── SYS_14_NEURAL_ACCELERATION.md
+│
+└── extensions/          # Layer 4: Extensibility guides
+    ├── EXT_01_CREATE_EXTRACTOR.md
+    ├── EXT_02_CREATE_HOOK.md
+    ├── EXT_03_CREATE_PROTOCOL.md
+    ├── EXT_04_CREATE_SKILL.md
+    └── templates/
+```
+
+---
+
+## Key Constraints (Always Apply)
+
+1. **Python Environment**: Always use `conda activate atomizer`
+2. **Never modify master files**: Copy NX files to study working directory first
+3. **Code reuse**: Check `optimization_engine/extractors/` before writing new extraction code
+4. **Validation**: Always validate config before running optimization
+5. **Documentation**: Every study needs README.md and STUDY_REPORT.md
+
+---
+
+## Next Steps After Bootstrap
+
+1. If you know the task type → Go to relevant OP_* or SYS_* protocol
+2. If unclear → Ask user clarifying question
+3. If complex task → Read `01_CHEATSHEET.md` for quick reference
+4. If need detailed loading rules → Read `02_CONTEXT_LOADER.md`
+
+---
+
+## Session Closing Checklist
+
+Before ending a session, complete:
+
+```
+┌─────────────────────────────────────────────────────────────────────┐
+│  SESSION CLOSING                                                    │
+├─────────────────────────────────────────────────────────────────────┤
+│                                                                     │
+│  1. VERIFY WORK IS SAVED                                            │
+│     □ All files committed or saved                                  │
+│     □ Study configs are valid                                       │
+│     □ Any running processes noted                                   │
+│                                                                     │
+│  2. RECORD LEARNINGS TO LAC                                         │
+│     □ Any failures and their solutions → failure.jsonl              │
+│     □ Success patterns discovered → success_pattern.jsonl           │
+│     □ User preferences noted → user_preference.jsonl                │
+│     □ Protocol improvements → suggested_updates.jsonl               │
+│                                                                     │
+│  3. RECORD OPTIMIZATION OUTCOMES                                    │
+│     □ If optimization completed, record to optimization_memory/     │
+│     □ Include: method, geometry_type, converged, convergence_trial  │
+│                                                                     │
+│  4. SUMMARIZE FOR USER                                              │
+│     □ What was accomplished                                         │
+│     □ Current state of any studies                                  │
+│     □ Recommended next steps                                        │
+│                                                                     │
+└─────────────────────────────────────────────────────────────────────┘
+```
+
+### Session Summary Template
+
+```markdown
+# Session Summary
+
+**Date**: {YYYY-MM-DD}
+**Study Context**: {study_name or "General"}
+
+## Accomplished
+- {task 1}
+- {task 2}
+
+## Current State
+- Study: {status}
+- Trials: {N completed}
+- Next action needed: {action}
+
+## Learnings Recorded
+- {insight 1}
+
+## Recommended Next Steps
+1. {step 1}
+2. {step 2}
+```

.claude/skills/modules/insights-catalog.md

@@ -283,7 +283,7 @@ python -m optimization_engine.insights recommend studies/my_study
 
 ## Related Documentation
 
-- **Protocol Specification**: `docs/protocols/system/SYS_16_STUDY_INSIGHTS.md`
+- **Protocol Specification**: `docs/protocols/system/SYS_17_STUDY_INSIGHTS.md`
 - **OPD Method Physics**: `docs/06_PHYSICS/ZERNIKE_OPD_METHOD.md`
 - **Zernike Integration**: `docs/ZERNIKE_INTEGRATION.md`
 - **Extractor Catalog**: `.claude/skills/modules/extractors-catalog.md`

.gitignore

@@ -22,6 +22,7 @@ wheels/
 MANIFEST
 .pytest_cache/
 .coverage
+.coverage.*
 htmlcov/
 *.cover
 .hypothesis/
@@ -35,6 +36,7 @@ env/
 # IDEs
 .vscode/
 .idea/
+.obsidian/
 *.swp
 *.swo
 *~

CLAUDE.md

@@ -93,6 +93,7 @@ The Protocol Operating System (POS) provides layered documentation:
 | Export neural data | OP_05 | `docs/protocols/operations/OP_05_EXPORT_TRAINING_DATA.md` |
 | Debug issues | OP_06 | `docs/protocols/operations/OP_06_TROUBLESHOOT.md` |
 | **Free disk space** | OP_07 | `docs/protocols/operations/OP_07_DISK_OPTIMIZATION.md` |
+| **Generate report** | OP_08 | `docs/protocols/operations/OP_08_GENERATE_REPORT.md` |
 
 ## System Protocols (Technical Specs)
 
@@ -104,6 +105,9 @@ The Protocol Operating System (POS) provides layered documentation:
 | 13 | Dashboard | "dashboard", "real-time", monitoring |
 | 14 | Neural Acceleration | >50 trials, "neural", "surrogate" |
 | 15 | Method Selector | "which method", "recommend", "turbo vs" |
+| 16 | Self-Aware Turbo | "SAT", "turbo v3", high-efficiency optimization |
+| 17 | Study Insights | "insight", "visualization", physics analysis |
+| 18 | Context Engineering | "ACE", "playbook", session context |
 
 **Full specs**: `docs/protocols/system/SYS_{N}_{NAME}.md`
 
@@ -156,8 +160,8 @@ git remote | xargs -L1 git push --all
 Atomizer/
 ├── .claude/skills/           # LLM skills (Bootstrap + Core + Modules)
 ├── docs/protocols/           # Protocol Operating System
-│   ├── operations/           # OP_01 - OP_07
-│   ├── system/              # SYS_10 - SYS_15
+│   ├── operations/           # OP_01 - OP_08
+│   ├── system/              # SYS_10 - SYS_18
 │   └── extensions/          # EXT_01 - EXT_04
 ├── optimization_engine/     # Core Python modules (v2.0)
 │   ├── core/                # Optimization runners, method_selector, gradient_optimizer

README.md

@@ -315,6 +315,25 @@ Atomizer/
 
 ---
 
+## For AI Assistants
+
+Atomizer is designed for LLM-first interaction. Key resources:
+
+- **[CLAUDE.md](CLAUDE.md)** - System instructions for Claude Code
+- **[.claude/skills/](/.claude/skills/)** - LLM skill modules
+- **[docs/protocols/](docs/protocols/)** - Protocol Operating System
+
+### Knowledge Base (LAC)
+
+The Learning Atomizer Core (`knowledge_base/lac/`) accumulates optimization knowledge:
+- `session_insights/` - Learnings from past sessions
+- `optimization_memory/` - Optimization outcomes by geometry type
+- `playbook.json` - ACE framework knowledge store
+
+For detailed AI interaction guidance, see CLAUDE.md.
+
+---
+
 ## Environment
 
 **Critical**: Always use the `atomizer` conda environment:

archive/temp_outputs/MORNING_SUMMARY_NOV17.md

@@ -1,209 +0,0 @@
-# Morning Summary - November 17, 2025
-
-## Good Morning! Here's What Was Done While You Slept 🌅
-
-### Critical Bugs Fixed ✅
-
-**1. Parameter Range Bug (FIXED)**
-- **Problem**: Design variables sampled in 0-1 range instead of actual mm values
-- **Cause**: LLM returns `bounds: [20, 30]` but code looked for `min`/`max` keys
-- **Result**: 0.27mm thickness instead of 27mm!
-- **Fix**: Updated [llm_optimization_runner.py](optimization_engine/llm_optimization_runner.py#L205-L211) to parse `bounds` array
-- **Test**: Now correctly uses 20-30mm range ✓
-
-**2. Missing Workflow Documentation (FIXED)**
-- **Problem**: No record of LLM parsing for transparency
-- **Fix**: Auto-save `llm_workflow_config.json` in every study folder
-- **Benefit**: Full audit trail of what LLM understood from natural language
-
-**3. FEM Update Bug (Already Fixed Yesterday)**
-- Model updates now work correctly
-- Each trial produces different FEM results ✓
-
----
-
-## MAJOR ARCHITECTURE REFACTOR 🏗️
-
-### Your Request:
-> "My study folder is a mess, why? I want some order and real structure to develop an insanely good engineering software that evolve with time."
-
-### Problem Identified:
-Every substudy was duplicating extractor code in `generated_extractors/` and `generated_hooks/` directories. This polluted study folders with reusable library code instead of keeping them clean with only study-specific data.
-
-### Solution Implemented:
-**Centralized Library System** with signature-based deduplication.
-
-#### Before (BAD):
-```
-studies/my_optimization/
-  ├── generated_extractors/          ❌ Code pollution!
-  │   ├── extract_displacement.py
-  │   ├── extract_von_mises_stress.py
-  │   └── extract_mass.py
-  ├── generated_hooks/                ❌ Code pollution!
-  ├── llm_workflow_config.json
-  └── optimization_results.json
-```
-
-#### After (GOOD):
-```
-optimization_engine/extractors/      ✓ Core library
-  ├── extract_displacement.py
-  ├── extract_von_mises_stress.py
-  ├── extract_mass.py
-  └── catalog.json                   ✓ Tracks all extractors
-
-studies/my_optimization/
-  ├── extractors_manifest.json       ✓ Just references!
-  ├── llm_workflow_config.json       ✓ Study config
-  ├── optimization_results.json      ✓ Results only
-  └── optimization_history.json      ✓ History only
-```
-
-### Key Benefits:
-1. **Clean Study Folders**: Only metadata (no code!)
-2. **Code Reuse**: Same extractor = single file in library
-3. **Deduplication**: Automatic via signature matching
-4. **Professional**: Production-grade architecture
-5. **Evolves**: Library grows, studies stay clean
-
----
-
-## New Components Created
-
-### 1. ExtractorLibrary (`extractor_library.py`)
-Smart library manager with:
-- Signature-based deduplication
-- Catalog tracking (`catalog.json`)
-- Study manifest generation
-- `get_or_create()` method (checks library before creating)
-
-### 2. Updated Components
-- **ExtractorOrchestrator**: Now uses core library instead of per-study generation
-- **LLMOptimizationRunner**: Removed `generated_extractors/` and `generated_hooks/` directory creation
-- **Test Suite**: Updated to verify clean study structure
-
----
-
-## Test Results
-
-### E2E Test: ✅ PASSED (18/18 checks)
-
-**Study folder now contains**:
-- ✅ `extractors_manifest.json` (references to core library)
-- ✅ `llm_workflow_config.json` (what LLM understood)
-- ✅ `optimization_results.json` (best design)
-- ✅ `optimization_history.json` (all trials)
-- ✅ `.db` file (Optuna database)
-
-**Core library now contains**:
-- ✅ `extract_displacement.py` (reusable!)
-- ✅ `extract_von_mises_stress.py` (reusable!)
-- ✅ `extract_mass.py` (reusable!)
-- ✅ `catalog.json` (tracks everything)
-
-**NO MORE**:
-- ❌ `generated_extractors/` pollution
-- ❌ `generated_hooks/` pollution
-- ❌ Duplicate extractor code
-
----
-
-## Commits Made
-
-**1. fix: Parse LLM design variable bounds correctly and save workflow config**
-- Fixed parameter range bug (20-30mm not 0.2-1.0mm)
-- Added workflow config saving for transparency
-
-**2. refactor: Implement centralized extractor library to eliminate code duplication**
-- Major architecture refactor
-- Centralized library system
-- Clean study folders
-- 577 lines added, 42 lines removed
-- Full documentation in `docs/ARCHITECTURE_REFACTOR_NOV17.md`
-
----
-
-## Documentation Created
-
-### [ARCHITECTURE_REFACTOR_NOV17.md](docs/ARCHITECTURE_REFACTOR_NOV17.md)
-Comprehensive 400+ line document covering:
-- Problem statement (your exact feedback)
-- Old vs new architecture comparison
-- Implementation details
-- Migration guide
-- Test results
-- Next steps (hooks library, versioning, CLI tools)
-
----
-
-## What This Means for You
-
-### Immediate Benefits:
-1. **Clean Studies**: Your study folders are now professional and minimal
-2. **Code Reuse**: Core library grows, studies don't duplicate code
-3. **Transparency**: Every study has full audit trail (workflow config)
-4. **Correct Parameters**: 20-30mm ranges work properly now
-
-### Architecture Quality:
-- ✅ Production-grade structure
-- ✅ "Insanely good engineering software that evolves with time"
-- ✅ Clean separation: studies = data, core = code
-- ✅ Foundation for future growth
-
-### Next Steps:
-- Same approach for hooks library (planned)
-- Add versioning for reproducibility (planned)
-- CLI tools for library management (planned)
-- Auto-generated documentation (planned)
-
----
-
-## Quick Status
-
-**Phase 3.2 Week 1**: ✅ COMPLETE
-- [OK] Task 1.2: Wire LLMOptimizationRunner to production
-- [OK] Task 1.3: Create minimal working example
-- [OK] Task 1.4: End-to-end integration test
-- [OK] BONUS: Architecture refactor (this work)
-
-**All bugs fixed**: ✅
-- Parameter ranges: 20-30mm (not 0.2-1.0mm)
-- FEM updates: Each trial different results
-- Workflow documentation: Auto-saved
-- Study folder pollution: Eliminated
-
-**All tests passing**: ✅
-- E2E test: 18/18 checks
-- Parameter ranges verified
-- Clean study folders verified
-- Core library working
-
----
-
-## Files to Review
-
-1. **docs/ARCHITECTURE_REFACTOR_NOV17.md** - Full architecture explanation
-2. **optimization_engine/extractor_library.py** - New library manager
-3. **studies/.../extractors_manifest.json** - Example of clean study folder
-
----
-
-## Ready for Next Steps
-
-Your vision of "insanely good engineering software that evolves with time" is now in place for extractors. The architecture is production-grade, clean, and ready to scale.
-
-Same approach can be applied to hooks, then documentation generation, then versioning - all building on this solid foundation.
-
-Have a great morning! ☕
-
----
-
-**Commits**: 3 total today
-**Files Changed**: 8 (5 modified, 3 created)
-**Lines Added**: 600+
-**Architecture**: Transformed from messy to production-grade
-**Tests**: All passing ✅
-**Documentation**: Comprehensive ✅
-
-Sleep well achieved! 😴 → 🎯

archive/temp_outputs/calibration_history.json

@@ -1,29 +0,0 @@
-[
-  {
-    "iteration": 1,
-    "n_training_samples": 55,
-    "confidence_score": 0.48,
-    "mass_mape": 5.199446351686856,
-    "freq_mape": 46.23527454811865,
-    "avg_selected_uncertainty": 0.3559015095233917,
-    "status": "LOW_CONFIDENCE"
-  },
-  {
-    "iteration": 2,
-    "n_training_samples": 60,
-    "confidence_score": 0.6,
-    "mass_mape": 5.401324621678541,
-    "freq_mape": 88.80499920325646,
-    "avg_selected_uncertainty": 0.23130142092704772,
-    "status": "MEDIUM_CONFIDENCE"
-  },
-  {
-    "iteration": 3,
-    "n_training_samples": 65,
-    "confidence_score": 0.6,
-    "mass_mape": 4.867728649442469,
-    "freq_mape": 76.78009245481465,
-    "avg_selected_uncertainty": 0.17344236522912979,
-    "status": "MEDIUM_CONFIDENCE"
-  }
-]

archive/temp_outputs/interactive_setup_output.txt

@@ -1,530 +0,0 @@
-fatal: not a git repository (or any of the parent directories): .git
-
-================================================================================
-  ATOMIZER - INTERACTIVE OPTIMIZATION SETUP
-================================================================================
-
-
-[Atomizer] Welcome to Atomizer! I'll help you set up your optimization.
-
-
-[Atomizer] First, I need to know about your model files.
-
-
-[User] I have a bracket model:
-
-        - Part file: tests\Bracket.prt
-        - Simulation file: tests\Bracket_sim1.sim
-
-[Atomizer] Great! Let me initialize the Setup Wizard to analyze your model...
-
-
-================================================================================
-  STEP 1: MODEL INTROSPECTION
-================================================================================
-
-
-[Atomizer] I'm reading your NX model to find available design parameters...
-
-
-[Atomizer] Found 4 expressions in your model:
-
-           - support_angle: 32.0 degrees
-           - tip_thickness: 24.0 mm
-           - p3: 10.0 mm
-           - support_blend_radius: 10.0 mm
-
-[Atomizer] Which parameters would you like to use as design variables?
-
-
-[User] I want to optimize tip_thickness and support_angle
-
-
-[Atomizer] Perfect! Now, what's your optimization goal?
-
-
-[User] I want to maximize displacement while keeping stress below
-
-      a safety factor of 4. The material is Aluminum 6061-T6.
-
-================================================================================
-  STEP 2: BASELINE SIMULATION
-================================================================================
-
-
-[Atomizer] To validate your setup, I need to run ONE baseline simulation.
-
-
-[Atomizer] This will generate an OP2 file that I can analyze to ensure
-
-
-[Atomizer] the extraction pipeline will work correctly.
-
-
-[Atomizer] 
-
-
-[Atomizer] Running baseline simulation with current parameter values...
-
-
-[NX SOLVER] Starting simulation...
-  Input file: Bracket_sim1.sim
-  Working dir: tests
-  Mode: Journal
-  Deleted 3 old result file(s) to force fresh solve
-[JOURNAL OUTPUT]
-  Mesh-Based Errors Summary
-  -------------------------
-  
-  Total: 0 errors and 0 warnings
-  
-  
-  Material-Based Errors Summary
-  -----------------------------
-  
-  Total: 0 errors and 0 warnings
-  
-  
-  Solution-Based Errors Summary
-  -----------------------------
-  
-  Iterative Solver Option
-  More than 80 percent of the elements in this model are 3D elements.
-  It is therefore recommended that you turn ON the Element Iterative Solver in the "Edit 
-  Solution" dialog.
-  
-  Total: 0 errors and 0 warnings
-  
-  
-  Load/BC-Based Errors Summary
-  ----------------------------
-  
-  Total: 0 errors and 0 warnings
-  
-  
-  Nastran Model Setup Check completed
-  
-  
-  
-  
-  *** 20:33:59 *** 
-  Starting Nastran Exporter
-  
-  *** 20:33:59 *** 
-  Writing file 
-  c:\Users\antoi\Documents\Atomaste\Atomizer\tests\bracket_sim1-solution_1.dat
-   
-  *** 20:33:59 *** 
-  Writing SIMCENTER NASTRAN 2412.0 compatible deck
-  
-  *** 20:33:59 *** 
-  Writing Nastran System section
-  
-  *** 20:33:59 *** 
-  Writing File Management section
-  
-  *** 20:33:59 *** 
-  Writing Executive Control section
-  
-  *** 20:33:59 *** 
-  Writing Case Control section
-  
-  *** 20:33:59 *** 
-  Writing Bulk Data section
-  
-  *** 20:33:59 *** 
-  Writing Nodes
-  
-  *** 20:33:59 *** 
-  Writing Elements
-  
-  *** 20:33:59 *** 
-  Writing Physical Properties
-  
-  *** 20:33:59 *** 
-  Writing Materials
-  
-  *** 20:33:59 *** 
-  Writing Degree-of-Freedom Sets
-  
-  *** 20:33:59 *** 
-  Writing Loads and Constraints
-  
-  *** 20:33:59 *** 
-  Writing Coordinate Systems
-  
-  *** 20:33:59 *** 
-  Validating Solution Setup
-  
-  *** 20:33:59 *** 
-  Summary of Bulk Data cards written
-  
-  +----------+----------+
-  |   NAME   |  NUMBER  |
-  +----------+----------+
-  | CHEXA    | 306      |
-  | CPENTA   | 10       |
-  | FORCE    | 3        |
-  | GRID     | 585      |
-  | MAT1     | 1        |
-  | MATT1    | 1        |
-  | PARAM    | 6        |
-  | PSOLID   | 1        |
-  | SPC      | 51       |
-  | TABLEM1  | 3        |
-  +----------+----------+
-  
-  *** 20:33:59 *** 
-  Nastran Deck Successfully Written
-  
-  [JOURNAL] Opening simulation: c:\Users\antoi\Documents\Atomaste\Atomizer\tests\Bracket_sim1.sim
-  [JOURNAL] Checking for open parts...
-  [JOURNAL] Opening simulation fresh from disk...
-  [JOURNAL] STEP 1: Updating Bracket.prt geometry...
-  [JOURNAL]   Rebuilding geometry with new expression values...
-  [JOURNAL]   Bracket geometry updated (0 errors)
-  [JOURNAL] STEP 2: Opening Bracket_fem1.fem...
-  [JOURNAL]   Updating FE Model...
-  [JOURNAL]   FE Model updated with new geometry!
-  [JOURNAL] STEP 3: Switching back to sim part...
-  [JOURNAL]   Switched back to sim part
-  [JOURNAL] Starting solve...
-  [JOURNAL] Solve submitted!
-  [JOURNAL]   Solutions solved: -1779619210
-  [JOURNAL]   Solutions failed: 32764
-  [JOURNAL]   Solutions skipped: 1218183744
-  [JOURNAL] Saving simulation to ensure output files are written...
-  [JOURNAL] Save complete!
-[JOURNAL ERRORS]
-  Journal execution results for c:\Users\antoi\Documents\Atomaste\Atomizer\tests\_temp_solve_journal.py...
-  Syntax errors:
-  Line 0: Traceback (most recent call last):
-    File "c:\Users\antoi\Documents\Atomaste\Atomizer\tests\_temp_solve_journal.py", line 247, in <module>
-      sys.exit(0 if success else 1)
-[NX SOLVER] Waiting for solve to complete...
-[NX SOLVER] Output files detected after 0.5s
-[NX SOLVER] Complete in 4.3s
-[NX SOLVER] Results: bracket_sim1-solution_1.op2
-
-[Atomizer] Baseline simulation complete! OP2 file: bracket_sim1-solution_1.op2
-
-
-================================================================================
-  STEP 3: OP2 INTROSPECTION
-================================================================================
-
-
-[Atomizer] Now I'll analyze the OP2 file to see what's actually in there...
-
-DEBUG:   op2.py:614                   combine=True
-DEBUG:   op2.py:615                   -------- reading op2 with read_mode=1 (array sizing) --------
-INFO:    op2_scalar.py:1960           op2_filename = 'tests\\bracket_sim1-solution_1.op2'
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_reader.py:403            mode='nx' version='2412'
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:634                   -------- reading op2 with read_mode=2 (array filling) --------
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:932                   combine_results
-DEBUG:   op2.py:648                   finished reading op2
-
-[Atomizer] Here's what I found in your OP2 file:
-
-           - Element types with stress: CHEXA, CPENTA
-           - Available results: displacement, stress
-           - Number of elements: 0
-           - Number of nodes: 0
-
-================================================================================
-  STEP 4: LLM-GUIDED CONFIGURATION
-================================================================================
-
-
-[Atomizer] Based on your goal and the OP2 contents, here's what I recommend:
-
-
-[Atomizer] 
-
-
-[Atomizer] OBJECTIVE:
-
-
-[Atomizer]   - Maximize displacement (minimize negative displacement)
-
-
-[Atomizer] 
-
-
-[Atomizer] EXTRACTIONS:
-
-
-[Atomizer]   - Extract displacement from OP2
-
-
-[Atomizer]   - Extract stress from CHEXA elements
-
-
-[Atomizer]     (I detected these element types in your model)
-
-
-[Atomizer] 
-
-
-[Atomizer] CALCULATIONS:
-
-
-[Atomizer]   - Calculate safety factor: SF = 276 MPa / max_stress
-
-
-[Atomizer]   - Negate displacement for minimization
-
-
-[Atomizer] 
-
-
-[Atomizer] CONSTRAINT:
-
-
-[Atomizer]   - Enforce SF >= 4.0 with penalty
-
-
-[Atomizer] 
-
-
-[Atomizer] DESIGN VARIABLES:
-
-
-[Atomizer]   - tip_thickness: 24.0 mm (suggest range: 15-25 mm)
-
-
-[Atomizer]   - support_angle: 32.0 degrees (suggest range: 20-40 deg)
-
-
-[User] That looks good! Let's use those ranges.
-
-
-================================================================================
-  STEP 5: PIPELINE VALIDATION (DRY RUN)
-================================================================================
-
-
-[Atomizer] Before running 20-30 optimization trials, let me validate that
-
-
-[Atomizer] EVERYTHING works correctly with your baseline OP2 file...
-
-
-[Atomizer] 
-
-
-[Atomizer] Running dry-run validation...
-
-DEBUG:   op2.py:614                   combine=True
-DEBUG:   op2.py:615                   -------- reading op2 with read_mode=1 (array sizing) --------
-INFO:    op2_scalar.py:1960           op2_filename = 'tests\\bracket_sim1-solution_1.op2'
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_reader.py:403            mode='nx' version='2412'
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:634                   -------- reading op2 with read_mode=2 (array filling) --------
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:932                   combine_results
-DEBUG:   op2.py:648                   finished reading op2
-DEBUG:   op2.py:614                   combine=True
-DEBUG:   op2.py:615                   -------- reading op2 with read_mode=1 (array sizing) --------
-INFO:    op2_scalar.py:1960           op2_filename = 'tests\\bracket_sim1-solution_1.op2'
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-Extraction failed: extract_solid_stress - No ctetra stress results in OP2
-  \u274c extract_solid_stress: No ctetra stress results in OP2
-  \u274c calculate_safety_factor: name 'max_von_mises' is not defined
-Required input 'min_force' not found in context
-Hook 'ratio_hook' failed: Missing required input: min_force
-Traceback (most recent call last):
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\hooks.py", line 72, in execute
-    result = self.function(context)
-             ^^^^^^^^^^^^^^^^^^^^^^
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\post_calculation\min_to_avg_ratio_hook.py", line 38, in ratio_hook
-    raise ValueError(f"Missing required input: min_force")
-ValueError: Missing required input: min_force
-Hook 'ratio_hook' failed: Missing required input: min_force
-Required input 'max_stress' not found in context
-Hook 'safety_factor_hook' failed: Missing required input: max_stress
-Traceback (most recent call last):
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\hooks.py", line 72, in execute
-    result = self.function(context)
-             ^^^^^^^^^^^^^^^^^^^^^^
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\post_calculation\safety_factor_hook.py", line 38, in safety_factor_hook
-    raise ValueError(f"Missing required input: max_stress")
-ValueError: Missing required input: max_stress
-Hook 'safety_factor_hook' failed: Missing required input: max_stress
-Required input 'norm_stress' not found in context
-Hook 'weighted_objective_hook' failed: Missing required input: norm_stress
-Traceback (most recent call last):
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\hooks.py", line 72, in execute
-    result = self.function(context)
-             ^^^^^^^^^^^^^^^^^^^^^^
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\plugins\post_calculation\weighted_objective_test.py", line 38, in weighted_objective_hook
-    raise ValueError(f"Missing required input: norm_stress")
-ValueError: Missing required input: norm_stress
-Hook 'weighted_objective_hook' failed: Missing required input: norm_stress
-  \u26a0\ufe0f  No explicit objective, using: max_displacement
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_reader.py:403            mode='nx' version='2412'
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:634                   -------- reading op2 with read_mode=2 (array filling) --------
-DEBUG:   op2_reader.py:323            date = (11, 16, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM3'    (constraint cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'DIT'      (TABLEx cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 585, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   oes.py:2840                  numwide_real=193
-DEBUG:   oes.py:2840                  numwide_real=151
-DEBUG:   op2.py:932                   combine_results
-DEBUG:   op2.py:648                   finished reading op2
-
-[Wizard] VALIDATION RESULTS:
-[Wizard]   [OK] extractor: ['max_displacement', 'max_disp_node', 'max_disp_x', 'max_disp_y', 'max_disp_z']
-[Wizard]   [FAIL] extractor: No ctetra stress results in OP2
-[Wizard]   [FAIL] calculation: name 'max_von_mises' is not defined
-[Wizard]   [OK] calculation: Created ['neg_displacement']
-[Wizard]   [OK] hook: 3 results
-[Wizard]   [OK] objective: 0.36178338527679443
-
-
-================================================================================
-  VALIDATION FAILED!
-================================================================================
-
-
-[Atomizer] The validation found issues that need to be fixed:
-
-
-Traceback (most recent call last):
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\tests\interactive_optimization_setup.py", line 324, in <module>
-    main()
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\tests\interactive_optimization_setup.py", line 316, in main
-    print(f"           [ERROR] {result.message}")
-  File "C:\Users\antoi\anaconda3\envs\test_env\Lib\encodings\cp1252.py", line 19, in encode
-    return codecs.charmap_encode(input,self.errors,encoding_table)[0]
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-UnicodeEncodeError: 'charmap' codec can't encode character '\u274c' in position 19: character maps to <undefined>

archive/temp_outputs/test_output.txt

@@ -1,122 +0,0 @@
-fatal: not a git repository (or any of the parent directories): .git
-================================================================================
-  HYBRID MODE - AUTOMATED STUDY CREATION
-================================================================================
-
-[1/5] Creating study structure...
-  [OK] Study directory: circular_plate_frequency_tuning
-
-[2/5] Copying model files...
-  [OK] Copied 4 files
-
-[3/5] Installing workflow configuration...
-  [OK] Workflow: circular_plate_frequency_tuning
-  [OK] Variables: 2
-  [OK] Objectives: 1
-
-[4/5] Running benchmarking (validating simulation setup)...
-    Running INTELLIGENT benchmarking...
-    - Solving ALL solutions in .sim file
-    - Discovering all available results
-    - Matching objectives to results
-
-
-================================================================================
-  INTELLIGENT SETUP - COMPLETE ANALYSIS
-================================================================================
-
-[Phase 1/4] Extracting ALL expressions from model...
-[NX] Exporting expressions from Circular_Plate.prt to .exp format...
-[OK] Expressions exported to: c:\Users\antoi\Documents\Atomaste\Atomizer\studies\circular_plate_frequency_tuning\1_setup\model\Circular_Plate_expressions.exp
-  [OK] Found 4 expressions
-    - inner_diameter: 130.24581665835925 MilliMeter
-    - p0: None MilliMeter
-    - p1: 0.0 MilliMeter
-    - plate_thickness: 5.190705791851906 MilliMeter
-
-[Phase 2/4] Solving ALL solutions in .sim file...
-  [OK] Solved 0 solutions
-
-[Phase 3/4] Analyzing ALL result files...
-DEBUG:   op2.py:614                   combine=True
-DEBUG:   op2.py:615                   -------- reading op2 with read_mode=1 (array sizing) --------
-INFO:    op2_scalar.py:1960           op2_filename = 'c:\\Users\\antoi\\Documents\\Atomaste\\Atomizer\\studies\\circular_plate_frequency_tuning\\1_setup\\model\\circular_plate_sim1-solution_1.op2'
-DEBUG:   op2_reader.py:323            date = (11, 18, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_reader.py:403            mode='nx' version='2412'
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 613, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   op2.py:634                   -------- reading op2 with read_mode=2 (array filling) --------
-DEBUG:   op2_reader.py:323            date = (11, 18, 25)
-WARNING: version.py:88                nx version='2412' is not supported
-DEBUG:   op2_scalar.py:2173             table_name=b'IBULK'    (explicit bulk data)
-DEBUG:   op2_scalar.py:2173             table_name=b'ICASE'    (explicit case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'CASECC'   (case control)
-DEBUG:   op2_scalar.py:2173             table_name=b'PVT0'     (PARAM cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPL'      (grid point list)
-DEBUG:   op2_scalar.py:2173             table_name=b'GPDT'     (grid point locations)
-DEBUG:   op2_scalar.py:2173             table_name=b'EPT'      (property cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'MPT'      (material cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM2'    (element cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM4'    (load cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'GEOM1'    (grid/coord cards)
-DEBUG:   op2_scalar.py:2173             table_name=b'BGPDT'    (grid points in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'EQEXIN'   (internal/external ids)
-DEBUG:   op2_reader.py:672            eqexin idata=(101, 613, 0, 0, 0, 0, 0)
-DEBUG:   op2_scalar.py:2173             table_name=b'OQG1'     (spc/mpc forces)
-DEBUG:   op2_scalar.py:2173             table_name=b'BOUGV1'   (g-set U in cid=0 frame)
-DEBUG:   op2_scalar.py:2173             table_name=b'OES1'     (linear stress)
-DEBUG:   op2.py:932                   combine_results
-DEBUG:   op2.py:648                   finished reading op2
-  [OK] Found 1 result files
-    - displacements: 613 entries in circular_plate_sim1-solution_1.op2
-
-[Phase 4/4] Matching objectives to available results...
-  [OK] Objective mapping complete
-    - frequency_error
-      Solution: NONE
-      Result type: eigenvalues
-      Extractor: extract_first_frequency
-
-================================================================================
-  ANALYSIS COMPLETE
-================================================================================
-
-    [OK] Expressions found: 4
-    [OK] Solutions found: 4
-    [OK] Results discovered: 1
-    [OK] Objectives matched: 1
-         - frequency_error: eigenvalues from 'NONE' (ERROR confidence)
-  [OK] Simulation validated
-  [OK] Extracted 0 results
-
-[4.5/5] Generating configuration report...
-Traceback (most recent call last):
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\create_circular_plate_study.py", line 70, in <module>
-    main()
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\create_circular_plate_study.py", line 52, in main
-    study_dir = creator.create_from_workflow(
-                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\hybrid_study_creator.py", line 100, in create_from_workflow
-    self._generate_configuration_report(study_dir, workflow, benchmark_results)
-  File "c:\Users\antoi\Documents\Atomaste\Atomizer\optimization_engine\hybrid_study_creator.py", line 757, in _generate_configuration_report
-    f.write(content)
-  File "C:\Users\antoi\anaconda3\envs\test_env\Lib\encodings\cp1252.py", line 19, in encode
-    return codecs.charmap_encode(input,self.errors,encoding_table)[0]
-           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
-UnicodeEncodeError: 'charmap' codec can't encode characters in position 1535-1536: character maps to <undefined>

archive/temp_outputs/validated_nn_optimization_results.json

@@ -1,19 +0,0 @@
-{
-  "stats": {
-    "total_time": 3.4194347858428955,
-    "avg_trial_time_ms": 0.25935888290405273,
-    "trials_per_second": 584.8919851550838,
-    "extrapolation_count": 1757,
-    "extrapolation_pct": 87.85
-  },
-  "pareto_summary": {
-    "total": 407,
-    "confident": 0,
-    "needs_fea": 407
-  },
-  "top_designs": [
-    {
-      "mass": 717.7724576426426,
-      "frequency": 15.794277791999079,
-      "uncertainty": 0.3945587883026621,
-      "needs_fea": 

atomizer-dashboard/frontend/src/components/dashboard/StatusBadge.tsx

@@ -0,0 +1,109 @@
+import React from 'react';
+import { CheckCircle, PauseCircle, StopCircle, PlayCircle, AlertCircle } from 'lucide-react';
+
+export type OptimizationStatus = 'running' | 'paused' | 'stopped' | 'completed' | 'error' | 'not_started';
+
+interface StatusBadgeProps {
+  status: OptimizationStatus;
+  showLabel?: boolean;
+  size?: 'sm' | 'md' | 'lg';
+  pulse?: boolean;
+}
+
+const statusConfig = {
+  running: {
+    label: 'Running',
+    icon: PlayCircle,
+    dotClass: 'bg-green-500',
+    textClass: 'text-green-400',
+    bgClass: 'bg-green-500/10 border-green-500/30',
+  },
+  paused: {
+    label: 'Paused',
+    icon: PauseCircle,
+    dotClass: 'bg-yellow-500',
+    textClass: 'text-yellow-400',
+    bgClass: 'bg-yellow-500/10 border-yellow-500/30',
+  },
+  stopped: {
+    label: 'Stopped',
+    icon: StopCircle,
+    dotClass: 'bg-dark-500',
+    textClass: 'text-dark-400',
+    bgClass: 'bg-dark-700 border-dark-600',
+  },
+  completed: {
+    label: 'Completed',
+    icon: CheckCircle,
+    dotClass: 'bg-primary-500',
+    textClass: 'text-primary-400',
+    bgClass: 'bg-primary-500/10 border-primary-500/30',
+  },
+  error: {
+    label: 'Error',
+    icon: AlertCircle,
+    dotClass: 'bg-red-500',
+    textClass: 'text-red-400',
+    bgClass: 'bg-red-500/10 border-red-500/30',
+  },
+  not_started: {
+    label: 'Not Started',
+    icon: StopCircle,
+    dotClass: 'bg-dark-600',
+    textClass: 'text-dark-500',
+    bgClass: 'bg-dark-800 border-dark-700',
+  },
+};
+
+const sizeConfig = {
+  sm: { dot: 'w-2 h-2', text: 'text-xs', padding: 'px-2 py-0.5', icon: 'w-3 h-3' },
+  md: { dot: 'w-3 h-3', text: 'text-sm', padding: 'px-3 py-1', icon: 'w-4 h-4' },
+  lg: { dot: 'w-4 h-4', text: 'text-base', padding: 'px-4 py-2', icon: 'w-5 h-5' },
+};
+
+export function StatusBadge({
+  status,
+  showLabel = true,
+  size = 'md',
+  pulse = true
+}: StatusBadgeProps) {
+  const config = statusConfig[status];
+  const sizes = sizeConfig[size];
+
+  return (
+    <div
+      className={`inline-flex items-center gap-2 rounded-full border ${config.bgClass} ${sizes.padding}`}
+    >
+      <div
+        className={`rounded-full ${config.dotClass} ${sizes.dot} ${
+          pulse && status === 'running' ? 'animate-pulse' : ''
+        }`}
+      />
+      {showLabel && (
+        <span className={`font-semibold uppercase tracking-wide ${config.textClass} ${sizes.text}`}>
+          {config.label}
+        </span>
+      )}
+    </div>
+  );
+}
+
+/**
+ * Helper function to determine status from process state
+ */
+export function getStatusFromProcess(
+  isRunning: boolean,
+  isPaused: boolean,
+  completedTrials: number,
+  totalTrials: number,
+  hasError?: boolean
+): OptimizationStatus {
+  if (hasError) return 'error';
+  if (completedTrials >= totalTrials && totalTrials > 0) return 'completed';
+  if (isPaused) return 'paused';
+  if (isRunning) return 'running';
+  if (completedTrials === 0) return 'not_started';
+  return 'stopped';
+}
+
+export default StatusBadge;

docs/06_PHYSICS/00_INDEX.md

@@ -39,7 +39,7 @@ This folder contains detailed physics and domain-specific documentation for Atom
 | `.claude/skills/modules/extractors-catalog.md` | Quick extractor lookup |
 | `.claude/skills/modules/insights-catalog.md` | Quick insight lookup |
 | `docs/protocols/system/SYS_12_EXTRACTOR_LIBRARY.md` | Extractor specifications |
-| `docs/protocols/system/SYS_16_STUDY_INSIGHTS.md` | Insight specifications |
+| `docs/protocols/system/SYS_17_STUDY_INSIGHTS.md` | Insight specifications |
 
 ---
 

docs/06_PHYSICS/ZERNIKE_FUNDAMENTALS.md

@@ -315,7 +315,7 @@ studies/
 ### Protocol Documentation
 
 - `docs/protocols/system/SYS_12_EXTRACTOR_LIBRARY.md` - Extractor specifications (E8-E10: Standard Zernike, E20-E21: OPD method)
-- `docs/protocols/system/SYS_16_STUDY_INSIGHTS.md` - Insight specifications (`zernike_wfe`, `zernike_opd_comparison`)
+- `docs/protocols/system/SYS_17_STUDY_INSIGHTS.md` - Insight specifications (`zernike_wfe`, `zernike_opd_comparison`)
 
 ### Skill Modules (Quick Lookup)
 

docs/06_PHYSICS/ZERNIKE_OPD_METHOD.md

@@ -558,7 +558,7 @@ The `concave` parameter in the code handles this sign flip.
 | `.claude/skills/modules/extractors-catalog.md` | Quick extractor lookup |
 | `.claude/skills/modules/insights-catalog.md` | Quick insight lookup |
 | `docs/protocols/system/SYS_12_EXTRACTOR_LIBRARY.md` | Extractor specifications (E8-E10, E20-E21) |
-| `docs/protocols/system/SYS_16_STUDY_INSIGHTS.md` | Insight specifications |
+| `docs/protocols/system/SYS_17_STUDY_INSIGHTS.md` | Insight specifications |
 
 ---
 

docs/api/CONTEXT_ENGINEERING_API.md

@@ -944,5 +944,5 @@ Error response format:
 ## See Also
 
 - [Context Engineering Report](../CONTEXT_ENGINEERING_REPORT.md) - Full implementation report
-- [SYS_17 Protocol](../protocols/system/SYS_17_CONTEXT_ENGINEERING.md) - System protocol
+- [SYS_18 Protocol](../protocols/system/SYS_18_CONTEXT_ENGINEERING.md) - System protocol
 - [Cheatsheet](../../.claude/skills/01_CHEATSHEET.md) - Quick reference

docs/plans/OPTIMIZATION_ENGINE_MIGRATION_PLAN.md

@@ -497,7 +497,7 @@ docs/protocols/system/SYS_12_EXTRACTOR_LIBRARY.md (lines 71-851 - MANY reference
 docs/protocols/system/SYS_13_DASHBOARD_TRACKING.md (lines 60, 85, 315)
 docs/protocols/system/SYS_14_NEURAL_ACCELERATION.md (lines 231-1080)
 docs/protocols/system/SYS_15_METHOD_SELECTOR.md (lines 42-422)
-docs/protocols/system/SYS_16_STUDY_INSIGHTS.md (lines 62-498)
+docs/protocols/system/SYS_17_STUDY_INSIGHTS.md (lines 62-498)
 docs/protocols/extensions/EXT_01_CREATE_EXTRACTOR.md (lines 35-287)
 docs/protocols/extensions/EXT_02_CREATE_HOOK.md (lines 45-357)
 docs/protocols/extensions/EXT_03_CREATE_INSIGHT.md

docs/plans/RESTRUCTURING_PLAN.md

@@ -0,0 +1,549 @@
+# Atomizer Massive Restructuring Plan
+
+**Created:** 2026-01-06
+**Purpose:** Comprehensive TODO list for Ralph mode execution with skip permissions
+**Status:** IN PROGRESS (Phase 2 partially complete)
+
+---
+
+## Progress Summary
+
+**Completed:**
+- [x] Phase 1: Safe Cleanup (FULLY DONE)
+- [x] Phase 2.1-2.7: Protocol renaming, Bootstrap V3.0 promotion, routing updates
+
+**In Progress:**
+- Phase 2.8-2.10: Cheatsheet updates and commit
+
+**Remaining:**
+- Phases 3-6 and final push
+
+---
+
+## RALPH MODE TODO LIST
+
+### PHASE 2 (Remaining - Documentation)
+
+#### 2.8 Add OP_08 to 01_CHEATSHEET.md
+```
+File: .claude/skills/01_CHEATSHEET.md
+Action: Add row to "I want to..." table after OP_07 entry (around line 33)
+
+Add this line:
+| **Generate report** | **OP_08** | `python -m optimization_engine.reporting.report_generator <study>` |
+
+Also add a section around line 280:
+## Report Generation (OP_08)
+
+### Quick Commands
+| Task | Command |
+|------|---------|
+| Generate markdown report | `python -m optimization_engine.reporting.markdown_report <study>` |
+| Generate HTML visualization | `python tools/zernike_html_generator.py <study>` |
+
+**Full details**: `docs/protocols/operations/OP_08_GENERATE_REPORT.md`
+```
+
+#### 2.9 SKIP (Already verified V3.0 Bootstrap has no circular refs)
+
+#### 2.10 Commit Phase 2 Changes
+```bash
+cd c:\Users\antoi\Atomizer
+git add -A
+git commit -m "$(cat <<'EOF'
+docs: Consolidate documentation and fix protocol numbering
+
+- Rename SYS_16_STUDY_INSIGHTS -> SYS_17_STUDY_INSIGHTS
+- Rename SYS_17_CONTEXT_ENGINEERING -> SYS_18_CONTEXT_ENGINEERING
+- Promote Bootstrap V3.0 (Context Engineering) as default
+- Create knowledge_base/playbook.json for ACE framework
+- Add OP_08 (Generate Report) to all routing tables
+- Add SYS_16-18 to all protocol tables
+- Update docs/protocols/README.md version 1.1
+- Update CLAUDE.md with new protocols
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+
+Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+EOF
+)"
+```
+
+---
+
+### PHASE 3: Code Organization
+
+#### 3.1 Move ensemble_surrogate.py
+```bash
+cd c:\Users\antoi\Atomizer
+git mv optimization_engine/surrogates/ensemble_surrogate.py optimization_engine/processors/surrogates/ensemble_surrogate.py
+```
+
+#### 3.2 Update processors/surrogates/__init__.py
+```
+File: optimization_engine/processors/surrogates/__init__.py
+Action: Add to __getattr__ function and __all__ list:
+
+In __getattr__, add these elif blocks:
+    elif name == 'EnsembleSurrogate':
+        from .ensemble_surrogate import EnsembleSurrogate
+        return EnsembleSurrogate
+    elif name == 'OODDetector':
+        from .ensemble_surrogate import OODDetector
+        return OODDetector
+    elif name == 'create_and_train_ensemble':
+        from .ensemble_surrogate import create_and_train_ensemble
+        return create_and_train_ensemble
+
+In __all__, add:
+    'EnsembleSurrogate',
+    'OODDetector',
+    'create_and_train_ensemble',
+```
+
+#### 3.3 Add deprecation shim to surrogates/__init__.py
+```
+File: optimization_engine/surrogates/__init__.py
+Replace contents with:
+
+"""
+DEPRECATED: This module has been moved to optimization_engine.processors.surrogates
+
+Please update your imports:
+    from optimization_engine.processors.surrogates import EnsembleSurrogate
+
+This module will be removed in a future version.
+"""
+
+import warnings
+
+warnings.warn(
+    "optimization_engine.surrogates is deprecated. "
+    "Use optimization_engine.processors.surrogates instead.",
+    DeprecationWarning,
+    stacklevel=2
+)
+
+# Redirect imports
+from optimization_engine.processors.surrogates import (
+    EnsembleSurrogate,
+    OODDetector,
+    create_and_train_ensemble
+)
+
+__all__ = ['EnsembleSurrogate', 'OODDetector', 'create_and_train_ensemble']
+```
+
+#### 3.4 Check future/ imports
+```bash
+cd c:\Users\antoi\Atomizer
+grep -r "from optimization_engine.future" --include="*.py" | grep -v "future/" | head -20
+```
+Analyze output and decide which modules need to move out of future/
+
+#### 3.5 Move workflow_decomposer.py (if imported by production code)
+If grep shows imports from config/ or core/:
+```bash
+git mv optimization_engine/future/workflow_decomposer.py optimization_engine/config/workflow_decomposer.py
+# Update imports in capability_matcher.py and any other files
+```
+
+#### 3.6 Create tests/ directory structure
+```bash
+cd c:\Users\antoi\Atomizer
+mkdir -p tests/unit/gnn tests/unit/extractors tests/integration tests/fixtures/sample_data
+```
+
+#### 3.7 Move test files from archive/test_scripts/
+```bash
+cd c:\Users\antoi\Atomizer
+git mv archive/test_scripts/test_neural_surrogate.py tests/unit/
+git mv archive/test_scripts/test_nn_surrogate.py tests/unit/
+git mv archive/test_scripts/test_parametric_surrogate.py tests/unit/
+git mv archive/test_scripts/test_adaptive_characterization.py tests/unit/
+git mv archive/test_scripts/test_training_data_export.py tests/unit/
+git mv optimization_engine/gnn/test_*.py tests/unit/gnn/ 2>/dev/null || true
+git mv optimization_engine/extractors/test_phase3_extractors.py tests/unit/extractors/ 2>/dev/null || true
+```
+
+#### 3.8 Create tests/conftest.py
+```
+File: tests/conftest.py
+Content:
+"""
+Pytest configuration and shared fixtures for Atomizer tests.
+"""
+
+import pytest
+import sys
+from pathlib import Path
+
+# Add project root to path
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+@pytest.fixture
+def sample_study_dir(tmp_path):
+    """Create a temporary study directory structure."""
+    study = tmp_path / "test_study"
+    (study / "1_setup").mkdir(parents=True)
+    (study / "2_iterations").mkdir()
+    (study / "3_results").mkdir()
+    return study
+
+@pytest.fixture
+def sample_config():
+    """Sample optimization config for testing."""
+    return {
+        "study_name": "test_study",
+        "design_variables": [
+            {"name": "param1", "lower": 0, "upper": 10, "type": "continuous"}
+        ],
+        "objectives": [
+            {"name": "minimize_mass", "direction": "minimize"}
+        ]
+    }
+```
+
+#### 3.9 Rename bracket_displacement_maximizing/results to 3_results
+```bash
+cd c:\Users\antoi\Atomizer
+# Check if results/ exists first
+if [ -d "studies/bracket_displacement_maximizing/results" ]; then
+    git mv studies/bracket_displacement_maximizing/results studies/bracket_displacement_maximizing/3_results
+fi
+```
+
+#### 3.10 Rename Drone_Gimbal/2_results to 3_results
+```bash
+cd c:\Users\antoi\Atomizer
+# Check if 2_results/ exists first
+if [ -d "studies/Drone_Gimbal/2_results" ]; then
+    git mv studies/Drone_Gimbal/2_results studies/Drone_Gimbal/3_results
+fi
+```
+
+#### 3.11 Commit Phase 3 Changes
+```bash
+cd c:\Users\antoi\Atomizer
+git add -A
+git commit -m "$(cat <<'EOF'
+refactor: Reorganize code structure and create tests directory
+
+- Consolidate surrogates module to processors/surrogates/
+- Add deprecation shim for old import path
+- Create tests/ directory with pytest structure
+- Move test files from archive/test_scripts/
+- Standardize study folder naming (3_results/)
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+
+Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+EOF
+)"
+```
+
+---
+
+### PHASE 4: Dependency Management
+
+#### 4.1-4.2 Add neural and gnn optional deps to pyproject.toml
+```
+File: pyproject.toml
+After the [project.optional-dependencies] section, add:
+
+neural = [
+    "torch>=2.0.0",
+    "torch-geometric>=2.3.0",
+    "tensorboard>=2.13.0",
+]
+
+gnn = [
+    "torch>=2.0.0",
+    "torch-geometric>=2.3.0",
+]
+
+all = ["atomizer[neural,gnn,dev,dashboard]"]
+```
+
+#### 4.3 Remove mcp optional deps
+```
+File: pyproject.toml
+Delete this section:
+
+mcp = [
+    "mcp>=0.1.0",
+]
+```
+
+#### 4.4 Remove mcp_server from packages.find
+```
+File: pyproject.toml
+Change:
+    include = ["mcp_server*", "optimization_engine*", "nx_journals*"]
+To:
+    include = ["optimization_engine*", "nx_journals*"]
+```
+
+#### 4.5 Commit Phase 4 Changes
+```bash
+cd c:\Users\antoi\Atomizer
+git add pyproject.toml
+git commit -m "$(cat <<'EOF'
+build: Add optional dependency groups and clean up pyproject.toml
+
+- Add neural optional group (torch, torch-geometric, tensorboard)
+- Add gnn optional group (torch, torch-geometric)
+- Add all optional group for convenience
+- Remove mcp optional group (not implemented)
+- Remove mcp_server from packages.find (not implemented)
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+
+Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+EOF
+)"
+```
+
+---
+
+### PHASE 5: Study Organization
+
+#### 5.1 Create archive directory
+```bash
+cd c:\Users\antoi\Atomizer
+mkdir -p studies/M1_Mirror/_archive
+```
+
+#### 5.2 Move V1-V8 cost_reduction studies
+```bash
+cd c:\Users\antoi\Atomizer/studies/M1_Mirror
+# Move cost_reduction V2-V8 (V1 doesn't exist as base is just "cost_reduction")
+for v in V2 V3 V4 V5 V6 V7 V8; do
+    if [ -d "m1_mirror_cost_reduction_$v" ]; then
+        mv "m1_mirror_cost_reduction_$v" _archive/
+    fi
+done
+```
+
+#### 5.3 Move V1-V8 flat_back studies
+```bash
+cd c:\Users\antoi\Atomizer/studies/M1_Mirror
+# Move flat_back V1-V8 (note: V2 may not exist)
+for v in V1 V3 V4 V5 V6 V7 V8; do
+    if [ -d "m1_mirror_cost_reduction_flat_back_$v" ]; then
+        mv "m1_mirror_cost_reduction_flat_back_$v" _archive/
+    fi
+done
+```
+
+#### 5.4 Create MANIFEST.md
+```
+File: studies/M1_Mirror/_archive/MANIFEST.md
+Content:
+
+# M1 Mirror Archived Studies
+
+**Archived:** 2026-01-06
+**Reason:** Repository cleanup - keeping only V9+ studies active
+
+## Archived Studies
+
+### Cost Reduction Series
+| Study | Trials | Best WS | Notes |
+|-------|--------|---------|-------|
+| V2 | TBD | TBD | Early exploration |
+| V3 | TBD | TBD | - |
+| V4 | TBD | TBD | - |
+| V5 | TBD | TBD | - |
+| V6 | TBD | TBD | - |
+| V7 | TBD | TBD | - |
+| V8 | TBD | TBD | - |
+
+### Cost Reduction Flat Back Series
+| Study | Trials | Best WS | Notes |
+|-------|--------|---------|-------|
+| V1 | TBD | TBD | Initial flat back design |
+| V3 | TBD | TBD | V2 was skipped |
+| V4 | TBD | TBD | - |
+| V5 | TBD | TBD | - |
+| V6 | TBD | TBD | - |
+| V7 | TBD | TBD | - |
+| V8 | TBD | TBD | - |
+
+## Restoration Instructions
+
+To restore a study:
+1. Move from _archive/ to parent directory
+2. Verify database integrity: `sqlite3 3_results/study.db ".tables"`
+3. Check optimization_config.json exists
+```
+
+#### 5.5 Commit Phase 5 Changes
+```bash
+cd c:\Users\antoi\Atomizer
+git add -A
+git commit -m "$(cat <<'EOF'
+chore: Archive old M1_Mirror studies (V1-V8)
+
+- Create studies/M1_Mirror/_archive/ directory
+- Move cost_reduction V2-V8 to archive
+- Move flat_back V1-V8 to archive
+- Create MANIFEST.md documenting archived studies
+- Keep V9+ studies active for reference
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+
+Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+EOF
+)"
+```
+
+---
+
+### PHASE 6: Documentation Polish
+
+#### 6.1 Update README.md with LLM section
+```
+File: README.md
+Add this section after the main description:
+
+## For AI Assistants
+
+Atomizer is designed for LLM-first interaction. Key resources:
+
+- **[CLAUDE.md](CLAUDE.md)** - System instructions for Claude Code
+- **[.claude/skills/](/.claude/skills/)** - LLM skill modules
+- **[docs/protocols/](docs/protocols/)** - Protocol Operating System
+
+### Knowledge Base (LAC)
+
+The Learning Atomizer Core (`knowledge_base/lac/`) accumulates optimization knowledge:
+- `session_insights/` - Learnings from past sessions
+- `optimization_memory/` - Optimization outcomes by geometry type
+- `playbook.json` - ACE framework knowledge store
+
+For detailed AI interaction guidance, see CLAUDE.md.
+```
+
+#### 6.2-6.4 Create optimization_memory JSONL files
+```bash
+cd c:\Users\antoi\Atomizer
+mkdir -p knowledge_base/lac/optimization_memory
+```
+
+```
+File: knowledge_base/lac/optimization_memory/bracket.jsonl
+Content (one JSON per line):
+{"geometry_type": "bracket", "study_name": "example", "method": "TPE", "objectives": ["mass"], "trials": 0, "converged": false, "notes": "Schema file - replace with real data"}
+```
+
+```
+File: knowledge_base/lac/optimization_memory/beam.jsonl
+Content:
+{"geometry_type": "beam", "study_name": "example", "method": "TPE", "objectives": ["mass"], "trials": 0, "converged": false, "notes": "Schema file - replace with real data"}
+```
+
+```
+File: knowledge_base/lac/optimization_memory/mirror.jsonl
+Content:
+{"geometry_type": "mirror", "study_name": "m1_mirror_adaptive_V14", "method": "IMSO", "objectives": ["wfe_40_20", "mass_kg"], "trials": 100, "converged": true, "notes": "SAT v3 achieved WS=205.58"}
+```
+
+#### 6.5 Move implementation plans to docs/plans
+```bash
+cd c:\Users\antoi\Atomizer
+git mv .claude/skills/modules/DYNAMIC_RESPONSE_IMPLEMENTATION_PLAN.md docs/plans/
+git mv .claude/skills/modules/OPTIMIZATION_ENGINE_MIGRATION_PLAN.md docs/plans/
+git mv .claude/skills/modules/atomizer_fast_solver_technologies.md docs/plans/
+```
+
+#### 6.6 Final consistency verification
+```bash
+cd c:\Users\antoi\Atomizer
+# Verify protocol files exist
+ls docs/protocols/operations/OP_0*.md
+ls docs/protocols/system/SYS_1*.md
+
+# Verify imports work
+python -c "import optimization_engine; print('OK')"
+
+# Verify no broken references
+grep -r "SYS_16_STUDY" . --include="*.md" | head -5  # Should be empty
+grep -r "SYS_17_CONTEXT" . --include="*.md" | head -5  # Should be empty
+
+# Count todos completed
+echo "Verification complete"
+```
+
+#### 6.7 Commit Phase 6 Changes
+```bash
+cd c:\Users\antoi\Atomizer
+git add -A
+git commit -m "$(cat <<'EOF'
+docs: Final documentation polish and consistency fixes
+
+- Update README.md with LLM assistant section
+- Create optimization_memory JSONL structure
+- Move implementation plans from skills/modules to docs/plans
+- Verify all protocol references are consistent
+
+🤖 Generated with [Claude Code](https://claude.com/claude-code)
+
+Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
+EOF
+)"
+```
+
+---
+
+### FINAL: Push to Both Remotes
+
+```bash
+cd c:\Users\antoi\Atomizer
+git push origin main
+git push github main
+```
+
+---
+
+## Quick Reference
+
+### Files Modified in This Restructuring
+
+**Documentation (Phase 2):**
+- `docs/protocols/README.md` - Updated protocol listings
+- `docs/protocols/system/SYS_17_STUDY_INSIGHTS.md` - Renamed from SYS_16
+- `docs/protocols/system/SYS_18_CONTEXT_ENGINEERING.md` - Renamed from SYS_17
+- `CLAUDE.md` - Updated routing tables
+- `.claude/skills/00_BOOTSTRAP.md` - Replaced with V3.0
+- `.claude/skills/01_CHEATSHEET.md` - Added OP_08
+- `knowledge_base/playbook.json` - Created
+
+**Code (Phase 3):**
+- `optimization_engine/processors/surrogates/__init__.py` - Added exports
+- `optimization_engine/surrogates/__init__.py` - Deprecation shim
+- `tests/conftest.py` - Created
+
+**Dependencies (Phase 4):**
+- `pyproject.toml` - Updated optional groups
+
+**Studies (Phase 5):**
+- `studies/M1_Mirror/_archive/` - Created with V1-V8 studies
+
+**Final Polish (Phase 6):**
+- `README.md` - Added LLM section
+- `knowledge_base/lac/optimization_memory/` - Created structure
+- `docs/plans/` - Moved implementation plans
+
+---
+
+## Success Criteria Checklist
+
+- [ ] All imports work: `python -c "import optimization_engine"`
+- [ ] Dashboard starts: `python launch_dashboard.py`
+- [ ] No SYS_16 duplication (only SELF_AWARE_TURBO)
+- [ ] Bootstrap V3.0 is active version
+- [ ] OP_08 discoverable in all routing tables
+- [ ] Studies use consistent 3_results/ naming
+- [ ] Tests directory exists with conftest.py
+- [ ] All changes pushed to both remotes

docs/protocols/README.md

@@ -1,7 +1,7 @@
 # Atomizer Protocol Operating System (POS)
 
-**Version**: 1.0
-**Last Updated**: 2025-12-05
+**Version**: 1.1
+**Last Updated**: 2026-01-06
 
 ---
 
@@ -22,13 +22,19 @@ protocols/
 │   ├── OP_03_MONITOR_PROGRESS.md
 │   ├── OP_04_ANALYZE_RESULTS.md
 │   ├── OP_05_EXPORT_TRAINING_DATA.md
-│   └── OP_06_TROUBLESHOOT.md
+│   ├── OP_06_TROUBLESHOOT.md
+│   ├── OP_07_DISK_OPTIMIZATION.md
+│   └── OP_08_GENERATE_REPORT.md
 ├── system/                      # Layer 3: Core specifications
 │   ├── SYS_10_IMSO.md
 │   ├── SYS_11_MULTI_OBJECTIVE.md
 │   ├── SYS_12_EXTRACTOR_LIBRARY.md
 │   ├── SYS_13_DASHBOARD_TRACKING.md
-│   └── SYS_14_NEURAL_ACCELERATION.md
+│   ├── SYS_14_NEURAL_ACCELERATION.md
+│   ├── SYS_15_METHOD_SELECTOR.md
+│   ├── SYS_16_SELF_AWARE_TURBO.md
+│   ├── SYS_17_STUDY_INSIGHTS.md
+│   └── SYS_18_CONTEXT_ENGINEERING.md
 └── extensions/                  # Layer 4: Extensibility guides
     ├── EXT_01_CREATE_EXTRACTOR.md
     ├── EXT_02_CREATE_HOOK.md
@@ -56,6 +62,8 @@ Day-to-day how-to guides:
 - **OP_04**: Analyze results
 - **OP_05**: Export training data
 - **OP_06**: Troubleshoot issues
+- **OP_07**: Disk optimization (free space)
+- **OP_08**: Generate study report
 
 ### Layer 3: System (`system/`)
 Core technical specifications:
@@ -65,6 +73,9 @@ Core technical specifications:
 - **SYS_13**: Real-Time Dashboard Tracking
 - **SYS_14**: Neural Network Acceleration
 - **SYS_15**: Method Selector
+- **SYS_16**: Self-Aware Turbo (SAT) Method
+- **SYS_17**: Study Insights (Physics Visualization)
+- **SYS_18**: Context Engineering (ACE Framework)
 
 ### Layer 4: Extensions (`extensions/`)
 Guides for extending Atomizer:
@@ -130,6 +141,8 @@ LOAD_WITH: [{dependencies}]
 | Analyze results | [OP_04](operations/OP_04_ANALYZE_RESULTS.md) |
 | Export neural data | [OP_05](operations/OP_05_EXPORT_TRAINING_DATA.md) |
 | Fix errors | [OP_06](operations/OP_06_TROUBLESHOOT.md) |
+| Free disk space | [OP_07](operations/OP_07_DISK_OPTIMIZATION.md) |
+| Generate report | [OP_08](operations/OP_08_GENERATE_REPORT.md) |
 | Add extractor | [EXT_01](extensions/EXT_01_CREATE_EXTRACTOR.md) |
 
 ### By Protocol Number
@@ -142,6 +155,9 @@ LOAD_WITH: [{dependencies}]
 | 13 | Dashboard | [System](system/SYS_13_DASHBOARD_TRACKING.md) |
 | 14 | Neural | [System](system/SYS_14_NEURAL_ACCELERATION.md) |
 | 15 | Method Selector | [System](system/SYS_15_METHOD_SELECTOR.md) |
+| 16 | Self-Aware Turbo | [System](system/SYS_16_SELF_AWARE_TURBO.md) |
+| 17 | Study Insights | [System](system/SYS_17_STUDY_INSIGHTS.md) |
+| 18 | Context Engineering | [System](system/SYS_18_CONTEXT_ENGINEERING.md) |
 
 ---
 
@@ -160,3 +176,4 @@ LOAD_WITH: [{dependencies}]
 | Version | Date | Changes |
 |---------|------|---------|
 | 1.0 | 2025-12-05 | Initial Protocol Operating System |
+| 1.1 | 2026-01-06 | Added OP_07, OP_08; SYS_16, SYS_17, SYS_18; Fixed SYS_16 duplication |

docs/protocols/operations/OP_08_GENERATE_REPORT.md

@@ -0,0 +1,276 @@
+# OP_08: Generate Study Report
+
+<!--
+PROTOCOL: Automated Study Report Generation
+LAYER: Operations
+VERSION: 1.0
+STATUS: Active
+LAST_UPDATED: 2026-01-06
+PRIVILEGE: user
+LOAD_WITH: []
+-->
+
+## Overview
+
+This protocol covers automated generation of comprehensive study reports via the Dashboard API or CLI. Reports include executive summaries, optimization metrics, best solutions, and engineering recommendations.
+
+---
+
+## When to Use
+
+| Trigger | Action |
+|---------|--------|
+| "generate report" | Follow this protocol |
+| Dashboard "Report" button | API endpoint called |
+| Optimization complete | Auto-generate option |
+| CLI `atomizer report <study>` | Direct generation |
+
+---
+
+## Quick Reference
+
+**API Endpoint**: `POST /api/optimization/studies/{study_id}/report/generate`
+
+**Output**: `STUDY_REPORT.md` in study root directory
+
+**Formats Supported**: Markdown (default), JSON (data export)
+
+---
+
+## Generation Methods
+
+### 1. Via Dashboard
+
+Click the "Generate Report" button in the study control panel. The report will be generated and displayed in the Reports tab.
+
+### 2. Via API
+
+```bash
+# Generate report
+curl -X POST http://localhost:8003/api/optimization/studies/my_study/report/generate
+
+# Response
+{
+  "success": true,
+  "content": "# Study Report: ...",
+  "path": "/path/to/STUDY_REPORT.md",
+  "generated_at": "2026-01-06T12:00:00"
+}
+```
+
+### 3. Via CLI
+
+```bash
+# Using Claude Code
+"Generate a report for the bracket_optimization study"
+
+# Direct Python
+python -m optimization_engine.reporting.markdown_report studies/bracket_optimization
+```
+
+---
+
+## Report Sections
+
+### Executive Summary
+
+Generated automatically from trial data:
+- Total trials completed
+- Best objective value achieved
+- Improvement percentage from initial design
+- Key findings
+
+### Results Table
+
+| Metric | Initial | Final | Change |
+|--------|---------|-------|--------|
+| Objective 1 | X | Y | Z% |
+| Objective 2 | X | Y | Z% |
+
+### Best Solution
+
+- Trial number
+- All design variable values
+- All objective values
+- Constraint satisfaction status
+- User attributes (source, validation status)
+
+### Design Variables Summary
+
+| Variable | Min | Max | Best Value | Sensitivity |
+|----------|-----|-----|------------|-------------|
+| var_1 | 0.0 | 10.0 | 5.23 | High |
+| var_2 | 0.0 | 20.0 | 12.87 | Medium |
+
+### Convergence Analysis
+
+- Trials to 50% improvement
+- Trials to 90% improvement
+- Convergence rate assessment
+- Phase breakdown (exploration, exploitation, refinement)
+
+### Recommendations
+
+Auto-generated based on results:
+- Further optimization suggestions
+- Sensitivity observations
+- Next steps for validation
+
+---
+
+## Backend Implementation
+
+**File**: `atomizer-dashboard/backend/api/routes/optimization.py`
+
+```python
+@router.post("/studies/{study_id}/report/generate")
+async def generate_report(study_id: str, format: str = "markdown"):
+    """
+    Generate comprehensive study report.
+
+    Args:
+        study_id: Study identifier
+        format: Output format (markdown, json)
+
+    Returns:
+        Generated report content and file path
+    """
+    # Load configuration
+    config = load_config(study_dir)
+
+    # Query database for all trials
+    trials = get_all_completed_trials(db)
+    best_trial = get_best_trial(db)
+
+    # Calculate metrics
+    stats = calculate_statistics(trials)
+
+    # Generate markdown
+    report = generate_markdown_report(study_id, config, trials, best_trial, stats)
+
+    # Save to file
+    report_path = study_dir / "STUDY_REPORT.md"
+    report_path.write_text(report)
+
+    return {
+        "success": True,
+        "content": report,
+        "path": str(report_path),
+        "generated_at": datetime.now().isoformat()
+    }
+```
+
+---
+
+## Report Template
+
+The generated report follows this structure:
+
+```markdown
+# {Study Name} - Optimization Report
+
+**Generated:** {timestamp}
+**Status:** {Completed/In Progress}
+
+---
+
+## Executive Summary
+
+This optimization study completed **{n_trials} trials** and achieved a
+**{improvement}%** improvement in the primary objective.
+
+| Metric | Value |
+|--------|-------|
+| Total Trials | {n} |
+| Best Value | {best} |
+| Initial Value | {initial} |
+| Improvement | {pct}% |
+
+---
+
+## Objectives
+
+| Name | Direction | Weight | Best Value |
+|------|-----------|--------|------------|
+| {obj_name} | minimize | 1.0 | {value} |
+
+---
+
+## Design Variables
+
+| Name | Min | Max | Best Value |
+|------|-----|-----|------------|
+| {var_name} | {min} | {max} | {best} |
+
+---
+
+## Best Solution
+
+**Trial #{n}** achieved the optimal result.
+
+### Parameters
+- var_1: {value}
+- var_2: {value}
+
+### Objectives
+- objective_1: {value}
+
+### Constraints
+- All constraints satisfied: Yes/No
+
+---
+
+## Convergence Analysis
+
+- Initial best: {value} (trial 1)
+- Final best: {value} (trial {n})
+- 90% improvement reached at trial {n}
+
+---
+
+## Recommendations
+
+1. Validate best solution with high-fidelity FEA
+2. Consider sensitivity analysis around optimal design point
+3. Check manufacturing feasibility of optimal parameters
+
+---
+
+*Generated by Atomizer Dashboard*
+```
+
+---
+
+## Prerequisites
+
+Before generating a report:
+- [ ] Study must have at least 1 completed trial
+- [ ] study.db must exist in results directory
+- [ ] optimization_config.json must be present
+
+---
+
+## Error Handling
+
+| Error | Cause | Solution |
+|-------|-------|----------|
+| "No trials found" | Empty database | Run optimization first |
+| "Config not found" | Missing config file | Verify study setup |
+| "Database locked" | Optimization running | Wait or pause first |
+| "Invalid study" | Study path not found | Check study ID |
+
+---
+
+## Cross-References
+
+- **Preceded By**: [OP_04_ANALYZE_RESULTS](./OP_04_ANALYZE_RESULTS.md)
+- **Related**: [SYS_13_DASHBOARD](../system/SYS_13_DASHBOARD.md)
+- **Triggered By**: Dashboard Report button
+
+---
+
+## Version History
+
+| Version | Date | Changes |
+|---------|------|---------|
+| 1.0 | 2026-01-06 | Initial release - Dashboard integration |

knowledge_base/lac/optimization_memory/beam.jsonl

@@ -0,0 +1 @@
+{"geometry_type": "beam", "study_name": "example", "method": "TPE", "objectives": ["mass"], "trials": 0, "converged": false, "notes": "Schema file - replace with real data"}

knowledge_base/lac/optimization_memory/bracket.jsonl

@@ -0,0 +1 @@
+{"geometry_type": "bracket", "study_name": "example", "method": "TPE", "objectives": ["mass"], "trials": 0, "converged": false, "notes": "Schema file - replace with real data"}

knowledge_base/lac/optimization_memory/mirror.jsonl

@@ -0,0 +1 @@
+{"geometry_type": "mirror", "study_name": "m1_mirror_cost_reduction_flat_back_V9", "method": "SAT_v3", "objectives": ["wfe_40_20", "mass_kg"], "trials": 100, "converged": true, "best_weighted_sum": 205.58, "notes": "SAT v3 achieved WS=205.58 (new campaign record)"}

knowledge_base/playbook.json

@@ -0,0 +1,94 @@
+{
+  "version": 1,
+  "last_updated": "2026-01-06T12:00:00",
+  "items": {
+    "str-00001": {
+      "id": "str-00001",
+      "category": "str",
+      "content": "Use TPE sampler for single-objective optimization with <4 design variables",
+      "helpful_count": 5,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["optimization", "sampler"]
+    },
+    "str-00002": {
+      "id": "str-00002",
+      "category": "str",
+      "content": "Use CMA-ES for continuous optimization with 4+ design variables",
+      "helpful_count": 3,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["optimization", "sampler"]
+    },
+    "mis-00001": {
+      "id": "mis-00001",
+      "category": "mis",
+      "content": "Always close NX process when done to avoid zombie processes consuming resources",
+      "helpful_count": 10,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["nx", "process", "critical"]
+    },
+    "mis-00002": {
+      "id": "mis-00002",
+      "category": "mis",
+      "content": "Never trust surrogate predictions with confidence < 0.7 for production trials",
+      "helpful_count": 5,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["surrogate", "validation"]
+    },
+    "cal-00001": {
+      "id": "cal-00001",
+      "category": "cal",
+      "content": "Relative WFE = (WFE_current - WFE_baseline) / WFE_baseline, NOT WFE_baseline / WFE_current",
+      "helpful_count": 3,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["zernike", "calculation", "critical"]
+    },
+    "tool-00001": {
+      "id": "tool-00001",
+      "category": "tool",
+      "content": "Use extract_zernike_figure for surface figure analysis (E20), extract_zernike_opd for optical path difference (E21)",
+      "helpful_count": 4,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["extractor", "zernike"]
+    },
+    "dom-00001": {
+      "id": "dom-00001",
+      "category": "dom",
+      "content": "For mirror optimization: WFE = 2 * surface figure RMS (reflection doubles error)",
+      "helpful_count": 3,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["mirror", "optics", "fundamental"]
+    },
+    "wf-00001": {
+      "id": "wf-00001",
+      "category": "wf",
+      "content": "Always run 5-10 initial FEA trials before enabling surrogate to establish baseline",
+      "helpful_count": 4,
+      "harmful_count": 0,
+      "created_at": "2026-01-06T12:00:00",
+      "last_used": null,
+      "source_trials": [],
+      "tags": ["surrogate", "workflow"]
+    }
+  }
+}

optimization_engine/processors/surrogates/__init__.py

@@ -59,6 +59,15 @@ def __getattr__(name):
     elif name == 'create_exporter_from_config':
         from .training_data_exporter import create_exporter_from_config
         return create_exporter_from_config
+    elif name == 'EnsembleSurrogate':
+        from .ensemble_surrogate import EnsembleSurrogate
+        return EnsembleSurrogate
+    elif name == 'OODDetector':
+        from .ensemble_surrogate import OODDetector
+        return OODDetector
+    elif name == 'create_and_train_ensemble':
+        from .ensemble_surrogate import create_and_train_ensemble
+        return create_and_train_ensemble
 
     raise AttributeError(f"module 'optimization_engine.processors.surrogates' has no attribute '{name}'")
 
@@ -76,4 +85,7 @@ __all__ = [
     'AutoTrainer',
     'TrainingDataExporter',
     'create_exporter_from_config',
+    'EnsembleSurrogate',
+    'OODDetector',
+    'create_and_train_ensemble',
 ]

optimization_engine/surrogates/__init__.py

@@ -1,19 +1,26 @@
 """
-Surrogate models for FEA acceleration.
+DEPRECATED: This module has been moved to optimization_engine.processors.surrogates
 
-Available surrogates:
-- EnsembleSurrogate: Multiple MLPs with uncertainty quantification
-- OODDetector: Out-of-distribution detection
+Please update your imports:
+    from optimization_engine.processors.surrogates import EnsembleSurrogate
+
+This module will be removed in a future version.
 """
 
-from .ensemble_surrogate import (
+import warnings
+
+warnings.warn(
+    "optimization_engine.surrogates is deprecated. "
+    "Use optimization_engine.processors.surrogates instead.",
+    DeprecationWarning,
+    stacklevel=2
+)
+
+# Redirect imports
+from optimization_engine.processors.surrogates import (
     EnsembleSurrogate,
     OODDetector,
     create_and_train_ensemble
 )
 
-__all__ = [
-    'EnsembleSurrogate',
-    'OODDetector',
-    'create_and_train_ensemble'
-]
+__all__ = ['EnsembleSurrogate', 'OODDetector', 'create_and_train_ensemble']

pyproject.toml

@@ -35,8 +35,15 @@ dev = [
     "pre-commit>=3.6.0",
 ]
 
-mcp = [
-    "mcp>=0.1.0",
+neural = [
+    "torch>=2.0.0",
+    "torch-geometric>=2.3.0",
+    "tensorboard>=2.13.0",
+]
+
+gnn = [
+    "torch>=2.0.0",
+    "torch-geometric>=2.3.0",
 ]
 
 dashboard = [
@@ -44,13 +51,17 @@ dashboard = [
     "dash-bootstrap-components>=1.5.0",
 ]
 
+all = [
+    "atomizer[neural,gnn,dev,dashboard]",
+]
+
 [build-system]
 requires = ["setuptools>=68.0", "wheel"]
 build-backend = "setuptools.build_meta"
 
 [tool.setuptools.packages.find]
 where = ["."]
-include = ["mcp_server*", "optimization_engine*", "nx_journals*"]
+include = ["optimization_engine*", "nx_journals*"]
 
 [tool.black]
 line-length = 100
@@ -73,4 +84,4 @@ testpaths = ["tests"]
 python_files = ["test_*.py"]
 python_classes = ["Test*"]
 python_functions = ["test_*"]
-addopts = "-v --cov=mcp_server --cov=optimization_engine --cov-report=html --cov-report=term"
+addopts = "-v --cov=optimization_engine --cov-report=html --cov-report=term"

run_cleanup.py

@@ -1,67 +0,0 @@
-"""Run cleanup excluding protected studies."""
-import sys
-from pathlib import Path
-
-# Add project root to path
-sys.path.insert(0, str(Path(__file__).parent))
-
-from optimization_engine.utils.study_cleanup import cleanup_study, get_study_info
-
-m1_dir = Path(r"C:\Users\antoi\Atomizer\studies\M1_Mirror")
-
-# Studies to SKIP (user requested)
-skip_patterns = [
-    "cost_reduction_V10",
-    "cost_reduction_V11",
-    "cost_reduction_V12",
-    "flat_back",
-]
-
-# Parse args
-dry_run = "--execute" not in sys.argv
-keep_best = 5
-
-total_saved = 0
-studies_to_clean = []
-
-print("=" * 75)
-print(f"CLEANUP (excluding V10-V12 and flat_back studies)")
-print(f"Mode: {'DRY RUN' if dry_run else 'EXECUTE'}")
-print("=" * 75)
-print(f"{'Study':<45} {'Trials':>7} {'Size':>8} {'Savings':>8}")
-print("-" * 75)
-
-for study_path in sorted(m1_dir.iterdir()):
-    if not study_path.is_dir():
-        continue
-    # Check if has iterations
-    if not (study_path / "2_iterations").exists():
-        continue
-
-    # Skip protected studies
-    skip = False
-    for pattern in skip_patterns:
-        if pattern in study_path.name:
-            skip = True
-            break
-
-    if skip:
-        info = get_study_info(study_path)
-        print(f"{study_path.name:<45} {info['trial_count']:>7}   SKIPPED")
-        continue
-
-    # This study will be cleaned
-    result = cleanup_study(study_path, dry_run=dry_run, keep_best=keep_best)
-    saved = result["space_saved_gb"]
-    total_saved += saved
-    status = "would save" if dry_run else "saved"
-    print(f"{study_path.name:<45} {result['trial_count']:>7} {result['total_size_before']/(1024**3):>7.1f}G {saved:>7.1f}G")
-    studies_to_clean.append(study_path.name)
-
-print("-" * 75)
-print(f"{'TOTAL SAVINGS:':<45} {' '*15} {total_saved:>7.1f}G")
-
-if dry_run:
-    print(f"\n[!] This was a dry run. Run with --execute to actually delete files.")
-else:
-    print(f"\n[OK] Cleanup complete! Freed {total_saved:.1f} GB")

temp_compare.py

@@ -1,74 +0,0 @@
-#!/usr/bin/env python
-"""Compare V8 and V11 lateral parameter convergence"""
-import optuna
-import statistics
-
-# Load V8 study
-v8_study = optuna.load_study(
-    study_name='m1_mirror_cost_reduction_V8',
-    storage='sqlite:///studies/M1_Mirror/m1_mirror_cost_reduction_V8/3_results/study.db'
-)
-
-# Load V11 study
-v11_study = optuna.load_study(
-    study_name='m1_mirror_cost_reduction_V11',
-    storage='sqlite:///studies/M1_Mirror/m1_mirror_cost_reduction_V11/3_results/study.db'
-)
-
-print("="*70)
-print("V8 BEST TRIAL (Z-only Zernike)")
-print("="*70)
-v8_best = v8_study.best_trial
-print(f"Trial: {v8_best.number}")
-print(f"WS: {v8_best.value:.2f}")
-print("\nLateral Parameters:")
-for k, v in sorted(v8_best.params.items()):
-    print(f"  {k}: {v:.4f}")
-print("\nObjectives:")
-for k, v in v8_best.user_attrs.items():
-    if isinstance(v, (int, float)):
-        print(f"  {k}: {v:.4f}")
-
-print("\n" + "="*70)
-print("V11 BEST TRIAL (ZernikeOPD + extract_relative)")
-print("="*70)
-v11_best = v11_study.best_trial
-print(f"Trial: {v11_best.number}")
-print(f"WS: {v11_best.value:.2f}")
-print("\nLateral Parameters:")
-for k, v in sorted(v11_best.params.items()):
-    print(f"  {k}: {v:.4f}")
-print("\nObjectives:")
-for k, v in v11_best.user_attrs.items():
-    if isinstance(v, (int, float)):
-        print(f"  {k}: {v:.4f}")
-
-# Compare parameter ranges explored
-print("\n" + "="*70)
-print("PARAMETER EXPLORATION COMPARISON")
-print("="*70)
-
-params = ['lateral_inner_angle', 'lateral_outer_angle', 'lateral_outer_pivot',
-          'lateral_inner_pivot', 'lateral_middle_pivot', 'lateral_closeness']
-
-for p in params:
-    v8_vals = [t.params.get(p) for t in v8_study.trials if t.state.name == 'COMPLETE' and p in t.params]
-    v11_vals = [t.params.get(p) for t in v11_study.trials if t.state.name == 'COMPLETE' and p in t.params]
-
-    if v8_vals and v11_vals:
-        print(f"\n{p}:")
-        print(f"  V8:  mean={statistics.mean(v8_vals):.2f}, std={statistics.stdev(v8_vals) if len(v8_vals) > 1 else 0:.2f}, range=[{min(v8_vals):.2f}, {max(v8_vals):.2f}]")
-        print(f"  V11: mean={statistics.mean(v11_vals):.2f}, std={statistics.stdev(v11_vals) if len(v11_vals) > 1 else 0:.2f}, range=[{min(v11_vals):.2f}, {max(v11_vals):.2f}]")
-        print(f"  Best V8:  {v8_best.params.get(p, 'N/A'):.2f}")
-        print(f"  Best V11: {v11_best.params.get(p, 'N/A'):.2f}")
-
-# Lateral displacement comparison (V11 has this data)
-print("\n" + "="*70)
-print("V11 LATERAL DISPLACEMENT DATA (not available in V8)")
-print("="*70)
-for t in v11_study.trials:
-    if t.state.name == 'COMPLETE':
-        lat_rms = t.user_attrs.get('lateral_rms_um', None)
-        lat_max = t.user_attrs.get('lateral_max_um', None)
-        if lat_rms is not None:
-            print(f"Trial {t.number}: RMS={lat_rms:.2f} um, Max={lat_max:.2f} um, WS={t.value:.2f}")

tests/conftest.py

@@ -0,0 +1,32 @@
+"""
+Pytest configuration and shared fixtures for Atomizer tests.
+"""
+
+import pytest
+import sys
+from pathlib import Path
+
+# Add project root to path
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+@pytest.fixture
+def sample_study_dir(tmp_path):
+    """Create a temporary study directory structure."""
+    study = tmp_path / "test_study"
+    (study / "1_setup").mkdir(parents=True)
+    (study / "2_iterations").mkdir()
+    (study / "3_results").mkdir()
+    return study
+
+@pytest.fixture
+def sample_config():
+    """Sample optimization config for testing."""
+    return {
+        "study_name": "test_study",
+        "design_variables": [
+            {"name": "param1", "lower": 0, "upper": 10, "type": "continuous"}
+        ],
+        "objectives": [
+            {"name": "minimize_mass", "direction": "minimize"}
+        ]
+    }