# 202607 — CX Exploration & Discovery Workshop

A **live facilitation aid** for a CX discovery session, built on the
[Mercury Notebook Deliverable Pattern](../../docs/Mercury_Notebook_Pattern_V1-00.md).
Unlike the TEI business-case studies, this deliverable computes no dollars —
its "numbers" are **topic status and progress**. The Mercury stage is the
visual you share on a call or in a workshop while you work through the
questions; the question script and captured notes live backstage and export
as LLM input for the survey write-up or a downstream business case.

## What the client sees (the stage)

A calm **topic board**: each topic, its one-line scope, a status glyph, and —
for the topic under discussion — a **live sub-topic checklist**, above a
**progress bar** ("3/8 topics complete"). No wall of questions: you ask those.

![board preview](docs/board_preview.png)

You drive it from the sidebar — a **status** selector and a **notes** box per
topic, plus a **checkbox** per sub-topic. As the conversation moves you set a
topic *In progress*, tick sub-topics as you cover them, mark it *Complete* (or
*Skipped*), and jot answers. Every change re-renders the board and progress bar
(Mercury re-runs the cells below the widgets).

## What you work from (backstage)

JupyterLab and the exports carry the **facilitator question script** (all 95
prompts, grouped by topic → sub-topic) and the **captured-session appendix**
(status + notes as a markdown table and one JSON block). Neither shows on the
Mercury stage. The 8 topics / 26 sub-topics / ~110-minute agenda are the
structured form of the source survey.

## Layout

```
discoverylib/           # the engine — all content & logic
  topics.py             #   the topic bank (verbatim anchor from the survey)
  session.py            #   status vocabulary, progress, checklist, export payload
  staging.py            #   stage/backstage detection (copied verbatim)
notebooks/cx_discovery.ipynb   # the deliverable (generated — see below)
scripts/
  build_notebook.py     #   regenerates the notebook from cell sources
  export_report.py      #   nbconvert → exports/*.html + *.md
tests/                  # engine pins + stage/backstage test
docs/cx_discovery_survey.md    # source survey (the original cxxm.md)
exports/                # generated report sources
```

## The notebook is generated

The notebook wires ~42 Mercury widgets (a status selector + notes box per
topic, a checkbox per sub-topic), all derived from the topic bank so they can't
drift from `discoverylib`. Rather than hand-maintain that JSON, the notebook is
built from readable cell sources in
[`scripts/build_notebook.py`](scripts/build_notebook.py):

```bash
python scripts/build_notebook.py      # regenerate after editing a cell
```

Edit facilitation *content* (topics, sub-topics, prompts, scope, minutes) in
[`discoverylib/topics.py`](discoverylib/topics.py) — not in the notebook.

## Run

```bash
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"

mercury --working-dir .                # serve the stage (share this screen)
jupyter lab                            # analyst / facilitator view
pytest                                 # engine pins + stage/backstage
jupyter nbconvert --to notebook --execute --inplace notebooks/cx_discovery.ipynb   # gate
python scripts/export_report.py        # exports/*.html + *.md for the LLM handoff
```

## Extending

New or reshaped discovery content is a `discoverylib/topics.py` edit, a test
pin (`tests/test_topics.py` recounts, `tests/test_session.py` for new logic),
then `python scripts/build_notebook.py`. Add a topic and the sidebar controls,
board, checklist, script, gate, and export all pick it up — because they're all
generated from the bank.