Add Siemens CT document evaluation scenario (three-step pipeline)

- scenarios/siemens_build/siemens-pdf-build.yaml: dataset build for all 17
  Siemens medical-imaging PDFs (aliyun_docmind parser, 10 questions/doc,
  failure_mode=skip, ~170 question total)
- scenarios/offline/siemens-pdf-offline-smoke.yaml: offline evaluation using
  source chunks as contexts and ground_truth as answer (up to 30 samples)
- scenarios/online/siemens-pdf-question-bank-online.yaml: online evaluation
  calling siemens_pdf_qa adapter, batch_size=4, up to 50 samples
- apps/siemens_pdf_qa/adapter.py: Siemens-specific adapter with bilingual
  (zh/en) system prompt and strict evidence-grounding for CT domain
- scripts/build_siemens_offline_smoke.py: helper to derive offline smoke CSV
  from completed dataset build artifacts (run after dataset build step)
- docs/superpowers/specs/2026-06-15-siemens-scenario-design.md: design spec

All three scenarios are automatically discovered by the web console.

Co-Authored-By: Claude Sonnet 4 <noreply@anthropic.com>

scenarios/online/siemens-pdf-question-bank-online.yaml

@@ -0,0 +1,22 @@
+scenario_name: siemens-pdf-question-bank-online
+mode: online
+dataset: ../../datasets/raw/generated/siemens-pdf-question-bank.csv
+judge_model: deepseek-v4-flash
+embedding_model: text-embedding-v3
+metrics:
+  - faithfulness
+  - answer_relevancy
+  - context_recall
+  - context_precision
+output_dir: ../../outputs/online/siemens-pdf-question-bank
+runtime:
+  batch_size: 4
+  app_concurrency: 4
+  metric_concurrency: 4
+  max_samples: 50
+app_adapter:
+  type: python
+  callable: apps.siemens_pdf_qa.adapter:run
+  static_kwargs:
+    source_chunks_path: ../../outputs/dataset-builds/siemens-pdf-question-bank/latest/source_chunks.jsonl
+    model: deepseek-v4-flash