Establish prompt engineering baseline with Gold Standard tests

- introduce Gold Standard evaluation corpus
- document decision taxonomy
- define prompt-engineering methodology
- add regression workflow
- establish Prompt Version 2 baseline
- validate decision_simple, decision_deferred and decision_none

tests/test_extraction_protocol.py

@@ -5,6 +5,7 @@ from pathlib import Path
 
 from src.meeting_lab.extraction.extract_chunks import (
     EXTRACTION_CATEGORIES,
+    build_prompt,
     extraction_path_for_chunk,
     normalize_current_schema,
     parse_json_response,
@@ -93,6 +94,14 @@ Final answer:
         self.assertEqual(parsed["facts"], ["final"])
         self.assertEqual(set(parsed), set(EXTRACTION_CATEGORIES))
 
+    def test_build_prompt_includes_common_and_decision_prompt_files(self) -> None:
+        prompt = build_prompt("transcript.txt", "Anna: Agreed.")
+
+        self.assertIn("Du extrahierst Informationen aus Meeting-Transkripten.", prompt)
+        self.assertIn("You extract decisions from meeting transcript text.", prompt)
+        self.assertIn("Extract each decision as one atomic commitment.", prompt)
+        self.assertIn("Anna: Agreed.", prompt)
+
     def test_build_protocol_groups_extraction_items(self) -> None:
         with tempfile.TemporaryDirectory() as directory:
             input_dir = Path(directory)