AI skill: SKILL.md, AI contract, scrubbed references, eval fixture (d)

- rpa-dashboard-ai/SKILL.md: trigger description and the shared question flow;
  points at the no-AI frontend.md, themes and palette instead of copying them.
- templates/contract.md: runs, review rows, endpoints and the server approve gate.
- Superbill extracts: patient names and the client name removed, every file
  carries an EXAMPLE ONLY banner. tests/test_reference_scan.py checks both skills
  for patient data, internal IPs, credentials and keys.
- tests/fixtures/d-ai-extraction and its eval entry, which runs page_check_ai
  on the built folder.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/fixtures/d-ai-extraction/extractor.py

@@ -0,0 +1,34 @@
+"""The LLM extraction call: one scanned invoice in, its fields out, each with word scores."""
+import json
+
+from google import genai
+from google.genai import types
+
+MODEL = "gemini-2.5-flash"
+FIELDS = {  # field name -> mandatory
+    "Invoice number": True,
+    "Invoice date": True,
+    "Vendor": True,
+    "PO number": False,
+    "Due date": True,
+    "Total": True,
+}
+PROMPT = (
+    "Read this invoice. Return JSON: a list of {field, value, word_scores}, one per field in "
+    + ", ".join(FIELDS)
+    + ". word_scores is your 0-1 legibility score for each word of the value. Use an empty "
+    "value and no scores when a field isn't on the page."
+)
+
+
+def extract_invoice(document: bytes, mime_type: str) -> list[dict]:
+    client = genai.Client()  # credentials come from the environment
+    response = client.models.generate_content(
+        model=MODEL,
+        contents=[types.Part.from_bytes(data=document, mime_type=mime_type), PROMPT],
+        config=types.GenerateContentConfig(response_mime_type="application/json"),
+    )
+    rows = json.loads(response.text)
+    for row in rows:
+        row["mandatory"] = FIELDS.get(row["field"], False)
+    return rows