chore: Project cleanup and Canvas UX improvements (Phase 7-9)

## Cleanup (v0.5.0)
- Delete 102+ orphaned MCP session temp files
- Remove build artifacts (htmlcov, dist, __pycache__)
- Archive superseded plan docs (RALPH_LOOP V2/V3, CANVAS V3, etc.)
- Move debug/analysis scripts from tests/ to tools/analysis/
- Archive redundant NX journals to archive/nx_journals/
- Archive monolithic PROTOCOL.md to docs/archive/
- Update .gitignore with missing patterns
- Clean old study files (optimization_log_old.txt, run_optimization_old.py)

## Canvas UX (Phases 7-9)
- Phase 7: Resizable panels with localStorage persistence
  - Left sidebar: 200-400px, Right panel: 280-600px
  - New useResizablePanel hook and ResizeHandle component
- Phase 8: Enable all palette items
  - All 8 node types now draggable
  - Singleton logic for model/solver/algorithm/surrogate
- Phase 9: Solver configuration
  - Add SolverEngine type (nxnastran, mscnastran, python, etc.)
  - Add NastranSolutionType (SOL101-SOL200)
  - Engine/solution dropdowns in config panel
  - Python script path support

## Documentation
- Update CHANGELOG.md with recent versions
- Update docs/00_INDEX.md
- Create examples/README.md
- Add docs/plans/CANVAS_UX_IMPROVEMENTS.md

tools/analysis/debug_insights.py

@@ -0,0 +1,50 @@
+"""Debug insights availability for a study."""
+import sys
+sys.path.insert(0, ".")
+from pathlib import Path
+
+# Test study path resolution
+study_id = 'm1_mirror_cost_reduction_V9'
+STUDIES_DIR = Path('studies')
+
+# Check nested path
+for topic_dir in STUDIES_DIR.iterdir():
+    if topic_dir.is_dir():
+        study_dir = topic_dir / study_id
+        if study_dir.exists():
+            print(f"Found study at: {study_dir}")
+            print(f"Has 1_setup: {(study_dir / '1_setup').exists()}")
+            print(f"Has 2_results: {(study_dir / '2_results').exists()}")
+
+            # Check what insights are available
+            from optimization_engine.insights import list_available_insights, get_configured_insights, recommend_insights_for_study
+
+            print("\n--- Available insights (can_generate=True) ---")
+            available = list_available_insights(study_dir)
+            print(f"Count: {len(available)}")
+            for a in available:
+                print(f"  - {a}")
+
+            print("\n--- Configured insights ---")
+            configured = get_configured_insights(study_dir)
+            print(f"Count: {len(configured)}")
+            for c in configured:
+                print(f"  - {c.type}: {c.name}")
+
+            print("\n--- Recommendations ---")
+            recs = recommend_insights_for_study(study_dir)
+            print(f"Count: {len(recs)}")
+            for r in recs:
+                print(f"  - {r['type']}: {r['name']}")
+
+            # Test individual insight can_generate
+            print("\n--- Testing each insight's can_generate ---")
+            from optimization_engine.insights import get_insight, list_insights
+
+            for info in list_insights():
+                insight = get_insight(info['type'], study_dir)
+                if insight:
+                    can = insight.can_generate()
+                    print(f"  {info['type']:20} can_generate={can}")
+
+            break