feat: add master notebook library scaffolding and review tooling

Add CLAUDE.md defining the Palladium master notebook conventions and
Red Panda Approval criteria, plus a review-notebook slash command for
LLM-driven notebook review.

Expand .gitignore to block client/engagement documents and generated
exports, keeping masters client-clean while allowing text/image sources.

Normalize slider widget numeric values from floats to integers in
notebook JSON.

assessments/CX_AI_Diagnostic/diaglib/export.py

@@ -0,0 +1,62 @@
+"""Structured engagement exports — the JSON is the source-of-truth artifact.
+
+``exports/{engagement_id}.json`` — the full Engagement, serialized.
+``exports/{engagement_id}.csv``  — one row per competency, for
+cross-engagement spreadsheet analysis (build spec §8).
+"""
+
+from __future__ import annotations
+
+import json
+from pathlib import Path
+
+import pandas as pd
+
+from .models import DiagnosticConfig, Engagement
+
+CSV_COLUMNS = [
+    "engagement_id", "client_name", "industry", "workshop_date",
+    "competency_id", "dimension", "score", "evidence",
+    "is_foundational", "is_binding_constraint",
+]
+
+
+def engagement_json(engagement: Engagement) -> str:
+    return json.dumps(engagement.model_dump(mode="json"), indent=2,
+                      ensure_ascii=False)
+
+
+def scores_dataframe(engagement: Engagement,
+                     config: DiagnosticConfig) -> pd.DataFrame:
+    binding = set(engagement.computed_value.binding_constraints
+                  if engagement.computed_value else [])
+    foundational = set(config.foundational_competencies)
+    rows = [{
+        "engagement_id": engagement.engagement_id,
+        "client_name": engagement.client_name,
+        "industry": engagement.industry_config,
+        "workshop_date": engagement.workshop_date.isoformat(),
+        "competency_id": s.competency_id,
+        "dimension": s.dimension,
+        "score": s.score,
+        "evidence": s.evidence,
+        "is_foundational": s.competency_id in foundational,
+        "is_binding_constraint": s.competency_id in binding,
+    } for s in engagement.scores]
+    return pd.DataFrame(rows, columns=CSV_COLUMNS)
+
+
+def write_exports(engagement: Engagement, config: DiagnosticConfig,
+                  exports_dir: Path) -> tuple[Path, Path]:
+    """Write both artifacts; returns ``(json_path, csv_path)``."""
+    exports_dir.mkdir(parents=True, exist_ok=True)
+    json_path = exports_dir / f"{engagement.engagement_id}.json"
+    csv_path = exports_dir / f"{engagement.engagement_id}.csv"
+    json_path.write_text(engagement_json(engagement), encoding="utf-8")
+    scores_dataframe(engagement, config).to_csv(csv_path, index=False)
+    return json_path, csv_path
+
+
+def load_engagement(json_path: Path) -> Engagement:
+    """Reload a saved engagement for review (acceptance §10 nice-to-have)."""
+    return Engagement.model_validate_json(json_path.read_text(encoding="utf-8"))