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/config.py

@@ -0,0 +1,77 @@
+"""Load and merge ``configs/*.yaml`` into a validated DiagnosticConfig.
+
+``base.yaml`` holds the industry-independent competency model; every other
+YAML in the directory is an industry overlay declaring ``extends: base``
+plus its value drivers and unlock costs. Merging is shallow and explicit:
+the overlay contributes industry identity, drivers, and costs; the base
+contributes everything else. Overlays may not redefine the competency
+model — one instrument, many industries.
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+from .models import DiagnosticConfig
+
+#: Overlay keys an industry file may set. Anything else (competencies,
+#: capping_heuristic, …) belongs in base.yaml and is rejected loudly.
+_OVERLAY_KEYS = {"extends", "industry", "display_name", "value_drivers", "unlock_costs"}
+
+
+def configs_dir(start: Path | None = None) -> Path:
+    """The study's ``configs/`` directory, found from ``start`` (or CWD).
+
+    Walks up so it works from the study root, ``notebooks/``, or ``tests/``.
+    """
+    here = (start or Path.cwd()).resolve()
+    for candidate in (here, *here.parents):
+        d = candidate / "configs"
+        if (d / "base.yaml").exists():
+            return d
+    raise FileNotFoundError("configs/base.yaml not found above " + str(here))
+
+
+def list_industries(directory: Path | None = None) -> list[str]:
+    """Industry config names (file stems), base excluded, sorted."""
+    d = directory or configs_dir()
+    return sorted(p.stem for p in d.glob("*.yaml") if p.stem != "base")
+
+
+def _read_yaml(path: Path) -> dict[str, Any]:
+    with open(path, encoding="utf-8") as fh:
+        data = yaml.safe_load(fh)
+    if not isinstance(data, dict):
+        raise ValueError(f"{path.name}: expected a mapping at top level")
+    return data
+
+
+def load_config(industry: str, directory: Path | None = None) -> DiagnosticConfig:
+    """Load ``base.yaml`` + the named industry overlay, validated."""
+    d = directory or configs_dir()
+    base = _read_yaml(d / "base.yaml")
+    overlay = _read_yaml(d / f"{industry}.yaml")
+
+    if overlay.get("extends") != "base":
+        raise ValueError(f"{industry}.yaml must declare 'extends: base'")
+    stray = set(overlay) - _OVERLAY_KEYS
+    if stray:
+        raise ValueError(
+            f"{industry}.yaml sets base-only keys {sorted(stray)} — "
+            "the competency model lives in base.yaml")
+
+    merged: dict[str, Any] = {
+        "version": base["version"],
+        "dimensions": base["dimensions"],
+        "competencies": base["competencies"],
+        "capping_heuristic": base["capping_heuristic"],
+        "foundational_competencies": base["foundational_competencies"],
+        "industry": overlay["industry"],
+        "display_name": overlay.get("display_name", overlay["industry"]),
+        "value_drivers": overlay.get("value_drivers") or [],
+        "unlock_costs": overlay.get("unlock_costs") or {},
+    }
+    return DiagnosticConfig.model_validate(merged)