Use Notebook signals in learner workbench

src/didactopus/learner_workbench.py

@@ -34,12 +34,18 @@ def _load_groundrecall_summary(pack_dir: Path) -> dict:
         }
     )
     top_rationales = [str(item.get("rationale", "")).strip() for item in review_candidates if str(item.get("rationale", "")).strip()][:3]
+    source_role_summary = payload.get("source_role_summary", {}) or {}
+    key_distinctions = payload.get("key_distinctions", []) or []
+    secondary_products = payload.get("review_context", {}).get("secondary_products", {}) if isinstance(payload.get("review_context"), dict) else {}
     return {
         "concept_id": concept.get("concept_id", ""),
         "concept_title": concept.get("title", ""),
         "review_candidate_count": len(review_candidates),
         "graph_codes": graph_codes,
         "top_rationales": top_rationales,
+        "source_role_summary": source_role_summary,
+        "key_distinctions": key_distinctions[:5],
+        "secondary_products": secondary_products,
     }
 
 
@@ -95,6 +101,23 @@ def _groundrecall_block(summary: dict) -> str:
     graph_codes = summary.get("graph_codes", []) or []
     if graph_codes:
         lines.append(f"- Structural signals: {', '.join(graph_codes)}")
+    source_role_summary = summary.get("source_role_summary", {}) or {}
+    if source_role_summary:
+        lines.append(
+            "- Source roles: "
+            + ", ".join(f"{role}={count}" for role, count in sorted(source_role_summary.items()))
+        )
+    for item in summary.get("key_distinctions", []) or []:
+        text = str(item.get("text", "")).strip()
+        distinction_type = str(item.get("distinction_type", "")).strip()
+        if text:
+            lines.append(f"- Distinction ({distinction_type or 'contrast'}): {text}")
+    secondary_products = summary.get("secondary_products", {}) or {}
+    if secondary_products:
+        lines.append(
+            "- Secondary review products: "
+            + ", ".join(f"{key}={value}" for key, value in sorted(secondary_products.items()) if value)
+        )
     for rationale in summary.get("top_rationales", []) or []:
         lines.append(f"- Review cue: {rationale}")
     return "\n".join(lines)

tests/test_learner_workbench.py

@@ -62,6 +62,15 @@ def test_build_pack_workbench_session_includes_groundrecall_context(monkeypatch,
             {
                 "bundle_kind": "groundrecall_query_bundle",
                 "concept": {"concept_id": "concept::question-framing", "title": "Question Framing"},
+                "source_role_summary": {"overview": 1, "argumentation": 1},
+                "key_distinctions": [
+                    {
+                        "claim_id": "clm_001",
+                        "distinction_type": "non_implication",
+                        "cue": "does not imply",
+                        "text": "A guiding question does not imply a settled interpretation.",
+                    }
+                ],
                 "review_candidates": [
                     {
                         "candidate_id": "concept::question-framing",
@@ -88,4 +97,8 @@ def test_build_pack_workbench_session_includes_groundrecall_context(monkeypatch,
 
     assert payload["groundrecall"]["review_candidate_count"] == 1
     assert payload["groundrecall"]["graph_codes"] == ["bridge_concept"]
+    assert payload["groundrecall"]["source_role_summary"]["overview"] == 1
+    assert payload["groundrecall"]["key_distinctions"][0]["distinction_type"] == "non_implication"
     assert "GroundRecall context:" in payload["mentor"]["text"]
+    assert "Source roles:" in payload["mentor"]["text"]
+    assert "Distinction" in payload["mentor"]["text"]