Scaffold: fork of Chambers architecture, renamed to Boardroom Map

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

assets/README.md

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+# Static assets bundled into the s9pk.
+# Nightshift has none yet; this keeps the default `assets/` ingredient present.

assets/instructions.md

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+# Boardroom Map
+
+Drop confidential documents in and convene a **panel of local LLMs** running on
+your DGX Sparks to review them. You choose the models, the personas (lenses), and
+how many reviews. An optional **local lead reviewer** synthesizes the panel into
+one consolidated report. There is **no frontier model and no cloud key** — in the
+default air-gapped mode the documents and their reviews never leave your hardware.
+
+Boardroom Map is a *control plane*: nothing serves or runs on your StartOS box (it only
+SSHes to the Sparks and extracts document text on CPU).
+
+## Setup (run the Actions in order)
+
+1. **Configure Sparks** — SSH host/user/key for your head Spark (and optionally a
+   second), plus the work directory and image tags. Then **Test Spark Connection**.
+2. **Configure Models** — the catalog of local models to serve (alias → HF id →
+   which Spark → port), and serving knobs. For air-gapped runs every model must be
+   on the **head Spark** and present in its HF cache.
+3. **Configure Reviewers** — the panel: one entry per review, each a model + a
+   persona (the lens it reads through) + an optional temperature.
+4. **Configure Review** — the rubric, the **Network Mode** (air-gapped vs
+   local-services), synthesis on/off + lead model, and whether to wipe documents
+   from the Sparks afterward.
+
+## Running a review
+
+1. Open the **Web UI** and drag your documents (PDF / DOCX / TXT / MD) onto the
+   inbox (or drop them in the service's `inbox` folder).
+2. Click **Run Review** (or enable *auto-run on drop*).
+3. Watch the activity log. The service extracts text locally, serves the needed
+   models on the Sparks **in waves** (so a panel can span more models than fit in
+   GPU memory at once), runs each reviewer, then the lead reviewer, and saves the
+   reports. Read them in the Web UI or via **View Latest Report**.
+
+## Network modes
+
+- **Air-gapped (default):** reviewer containers join an `--internal` Docker
+  network — they can reach only the on-Spark model proxy, with zero internet
+  egress. Models are served from a pre-pulled HF cache. All models must be on the
+  head Spark. Strongest confidentiality.
+- **Local services:** reviewers may also reach LAN services (e.g. SearXNG) and the
+  second Spark. This network has egress unless you firewall it — use only when you
+  accept that reviewers can reach the network.
+
+The original documents are extracted to plain text on the StartOS box; only that
+text is shipped to the Sparks, and it is wiped from the Sparks after the job (the
+reports are kept on your StartOS box).