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_Discovery_Workshop/scripts/export_report.py

@@ -0,0 +1,123 @@
+"""Export the discovery notebook as an LLM-readable report source.
+
+Executes the notebook ONCE (widget defaults — or whatever you've captured
+and saved in the notebook), then converts the executed copy twice:
+
+  exports/cx_discovery.html  — human-reviewable, full presentation
+  exports/cx_discovery.md    — leanest LLM input: presentation-tagged cells
+                               (setup, widgets, board) are stripped, a
+                               framing preamble is prepended, and the data
+                               appendix ends the file with one fenced JSON
+                               block — the machine source of truth.
+
+Engagement identity (client, date, facilitator) is read from the notebook's
+``engagement-data`` cell and stamped into the preamble.
+
+Run from the study root:  python scripts/export_report.py
+"""
+from __future__ import annotations
+
+import subprocess
+import sys
+import tempfile
+from pathlib import Path
+from typing import Any
+
+ROOT = Path(__file__).resolve().parent.parent
+NOTEBOOK = ROOT / "notebooks" / "cx_discovery.ipynb"
+EXPORTS = ROOT / "exports"
+
+# Cells tagged with any of these never reach the .md export — they are
+# stage presentation (source and widget-repr noise), not session record.
+STRIP_TAGS_FROM_MD = '{"presentation"}'
+
+
+def engagement_data() -> dict[str, Any]:
+    """Exec the engagement-data cell (same trick as tests/conftest.py)."""
+    import nbformat
+
+    nb = nbformat.read(NOTEBOOK, as_version=4)
+    cells = [c for c in nb.cells
+             if "engagement-data" in c.metadata.get("tags", [])]
+    assert len(cells) == 1, "expected exactly one engagement-data cell"
+    ns: dict[str, Any] = {}
+    exec(compile(cells[0].source, f"{NOTEBOOK.name} [engagement-data]", "exec"), ns)
+    return ns["ENGAGEMENT"]  # type: ignore[no-any-return]
+
+
+def preamble() -> str:
+    eng = engagement_data()
+    who = " · ".join(str(eng[k]).strip()
+                     for k in ("client", "workshop_date", "facilitator")
+                     if str(eng.get(k, "")).strip())
+    attendees = ", ".join(str(a) for a in eng.get("attendees", ()) or ())
+    if who:
+        line = who + (f" — attendees: {attendees}" if attendees else "")
+    else:
+        line = "master copy — placeholders; no engagement captured."
+    return "\n".join([
+        "<!-- Export preamble — generated by scripts/export_report.py -->",
+        "**What this is** — the exported record of a CX Exploration & Discovery",
+        "workshop session, produced from the Mercury-served notebook that ran the",
+        "session. It is LLM input for drafting the survey write-up or seeding a",
+        "business case.",
+        "",
+        f"**Engagement** — {line}",
+        "",
+        "**How to read it** — first the workshop content as annotated source (the",
+        "topic bank, then the engagement data), then the facilitation script",
+        "(every prompt, grouped by topic and sub-topic), the verification gate,",
+        "and finally the captured-session record: the per-topic table (status,",
+        "covered sub-topics, notes) and — last — **Session state (JSON)**, one",
+        "fenced `json` block. Where prose and JSON disagree, the JSON block is",
+        "the source of truth.",
+        "",
+        "---",
+        "",
+        "",
+    ])
+
+
+def main() -> None:
+    if len(sys.argv) > 1 and sys.argv[1] not in NOTEBOOK.name:
+        sys.exit(f"no notebook matches {sys.argv[1]!r}")
+    EXPORTS.mkdir(exist_ok=True)
+
+    with tempfile.TemporaryDirectory() as tmp:
+        executed = Path(tmp) / NOTEBOOK.name
+        # 1. Execute once — both formats convert the same session state.
+        # (Never combine --execute with TagRemovePreprocessor in one call:
+        # the cell could be stripped before it runs.)
+        subprocess.run(
+            [sys.executable, "-m", "nbconvert", "--execute",
+             "--to", "notebook", "--output", str(executed), str(NOTEBOOK)],
+            check=True, cwd=ROOT,
+        )
+        # 2. HTML — full presentation, human review artifact.
+        subprocess.run(
+            [sys.executable, "-m", "nbconvert", "--to", "html",
+             "--output-dir", str(EXPORTS), "--output", NOTEBOOK.stem,
+             str(executed)],
+            check=True, cwd=ROOT,
+        )
+        # 3. Markdown — LLM artifact: strip presentation cells.
+        subprocess.run(
+            [sys.executable, "-m", "nbconvert", "--to", "markdown",
+             "--output-dir", str(EXPORTS), "--output", NOTEBOOK.stem,
+             "--TagRemovePreprocessor.enabled=True",
+             f"--TagRemovePreprocessor.remove_cell_tags={STRIP_TAGS_FROM_MD}",
+             str(executed)],
+            check=True, cwd=ROOT,
+        )
+
+    # 4. Prepend the framing preamble to the markdown export.
+    md = EXPORTS / f"{NOTEBOOK.stem}.md"
+    md.write_text(preamble() + md.read_text(encoding="utf-8"), encoding="utf-8")
+
+    for p in sorted(EXPORTS.iterdir()):
+        if p.suffix in (".html", ".md"):
+            print(f"wrote {p.relative_to(ROOT)} ({p.stat().st_size / 1024:,.0f} KB)")
+
+
+if __name__ == "__main__":
+    main()