researchers/web/agent.py

@@ -19,7 +19,6 @@ from researchers.web.models import (
     DiscoveryEvent,
     Gap,
     GapCategory,
-    OpenQuestion,
     ResearchConstraints,
     ResearchResult,
 )
@@ -94,14 +93,6 @@ Produce a JSON object with these exact fields:
       "source_locator": "URL where you found this, or null"
     }}
   ],
-  "open_questions": [
-    {{
-      "question": "A follow-up question that emerged from the research",
-      "context": "What evidence prompted this question",
-      "priority": "high|medium|low",
-      "source_locator": "URL where this question arose, or null"
-    }}
-  ],
   "confidence": 0.0-1.0,
   "confidence_factors": {{
     "num_corroborating_sources": 0,
@@ -515,16 +506,6 @@ class WebResearcher:
                 for d in data.get("discovery_events", [])
             ]
 
-            open_questions = [
-                OpenQuestion(
-                    question=q.get("question", ""),
-                    context=q.get("context", ""),
-                    priority=q.get("priority", "medium"),
-                    source_locator=q.get("source_locator"),
-                )
-                for q in data.get("open_questions", [])
-            ]
-
             cf = data.get("confidence_factors", {})
             confidence_factors = ConfidenceFactors(
                 num_corroborating_sources=cf.get("num_corroborating_sources", 0),
@@ -540,7 +521,6 @@ class WebResearcher:
                 citations=citations,
                 gaps=gaps,
                 discovery_events=discovery_events,
-                open_questions=open_questions,
                 confidence=data.get("confidence", 0.5),
                 confidence_factors=confidence_factors,
                 cost_metadata=CostMetadata(

researchers/web/models.py

@@ -132,35 +132,6 @@ class DiscoveryEvent(BaseModel):
     )
 
 
-# ---------------------------------------------------------------------------
-# Output types — OpenQuestion
-# ---------------------------------------------------------------------------
-
-
-class OpenQuestion(BaseModel):
-    """A follow-up question that emerged from the research.
-
-    Distinct from gaps (what failed) and discovery events (what's lateral).
-    Open questions look forward: "based on what I found, this needs deeper
-    investigation." The PI uses these to decide whether to dispatch
-    additional research calls.
-    """
-
-    question: str = Field(
-        description="The follow-up question that emerged from the research.",
-    )
-    context: str = Field(
-        description="What evidence or finding prompted this question.",
-    )
-    priority: str = Field(
-        description="'high' (critical to answer quality), 'medium' (would improve answer), 'low' (nice to know).",
-    )
-    source_locator: Optional[str] = Field(
-        default=None,
-        description="URL or source where this question arose from.",
-    )
-
-
 # ---------------------------------------------------------------------------
 # Output types — Confidence
 # ---------------------------------------------------------------------------
@@ -244,10 +215,6 @@ class ResearchResult(BaseModel):
         default_factory=list,
         description="Lateral findings for other researchers.",
     )
-    open_questions: list[OpenQuestion] = Field(
-        default_factory=list,
-        description="Follow-up questions that emerged from the research.",
-    )
     confidence: float = Field(
         ge=0.0,
         le=1.0,

tests/test_agent.py

@@ -70,14 +70,6 @@ VALID_SYNTHESIS_JSON = json.dumps(
                 "source_locator": "https://example.com/ref",
             }
         ],
-        "open_questions": [
-            {
-                "question": "What is the optimal irrigation schedule for high-elevation potatoes?",
-                "context": "Multiple sources mention irrigation is critical but none specify schedules.",
-                "priority": "medium",
-                "source_locator": "https://example.com/utah-crops",
-            }
-        ],
         "confidence": 0.82,
         "confidence_factors": {
             "num_corroborating_sources": 3,
@@ -205,8 +197,6 @@ class TestWebResearcher:
             assert len(result.gaps) == 1
             assert result.gaps[0].category == "source_not_found"
             assert len(result.discovery_events) == 1
-            assert len(result.open_questions) == 1
-            assert "irrigation" in result.open_questions[0].question
             assert result.confidence == 0.82
             assert result.confidence_factors.num_corroborating_sources == 3
             assert result.cost_metadata.model_id == "claude-test"

tests/test_models.py

@@ -13,7 +13,6 @@ from researchers.web.models import (
     DiscoveryEvent,
     Gap,
     GapCategory,
-    OpenQuestion,
     ResearchConstraints,
     ResearchResult,
 )
@@ -59,17 +58,6 @@ def make_discovery_event(**overrides) -> DiscoveryEvent:
     return DiscoveryEvent(**defaults)
 
 
-def make_open_question(**overrides) -> OpenQuestion:
-    defaults = {
-        "question": "What is the optimal irrigation schedule for high-elevation potatoes?",
-        "context": "Multiple sources mention irrigation is critical but none specify schedules.",
-        "priority": "medium",
-        "source_locator": "https://example.com/utah-crops",
-    }
-    defaults.update(overrides)
-    return OpenQuestion(**defaults)
-
-
 def make_confidence_factors(**overrides) -> ConfidenceFactors:
     defaults = {
         "num_corroborating_sources": 3,
@@ -101,7 +89,6 @@ def make_research_result(**overrides) -> ResearchResult:
         "citations": [make_citation()],
         "gaps": [make_gap()],
         "discovery_events": [make_discovery_event()],
-        "open_questions": [make_open_question()],
         "confidence": 0.82,
         "confidence_factors": make_confidence_factors(),
         "cost_metadata": make_cost_metadata(),
@@ -263,33 +250,6 @@ class TestDiscoveryEvent:
         assert e == e2
 
 
-# ---------------------------------------------------------------------------
-# OpenQuestion
-# ---------------------------------------------------------------------------
-
-
-class TestOpenQuestion:
-    def test_full_question(self):
-        q = make_open_question()
-        assert "irrigation" in q.question
-        assert q.priority == "medium"
-        assert q.source_locator is not None
-
-    def test_minimal_question(self):
-        q = OpenQuestion(
-            question="Is this viable?",
-            context="Found conflicting data.",
-            priority="low",
-        )
-        assert q.source_locator is None
-
-    def test_serialization_roundtrip(self):
-        q = make_open_question()
-        data = q.model_dump()
-        q2 = OpenQuestion(**data)
-        assert q == q2
-
-
 # ---------------------------------------------------------------------------
 # ConfidenceFactors
 # ---------------------------------------------------------------------------
@@ -365,18 +325,16 @@ class TestResearchResult:
         assert len(r.citations) == 1
         assert len(r.gaps) == 1
         assert len(r.discovery_events) == 1
-        assert len(r.open_questions) == 1
         assert 0.0 <= r.confidence <= 1.0
         assert r.cost_metadata.model_id == "claude-sonnet-4-6"
 
     def test_empty_lists_allowed(self):
         r = make_research_result(
-            citations=[], gaps=[], discovery_events=[], open_questions=[]
+            citations=[], gaps=[], discovery_events=[]
         )
         assert r.citations == []
         assert r.gaps == []
         assert r.discovery_events == []
-        assert r.open_questions == []
 
     def test_confidence_bounds(self):
         with pytest.raises(ValidationError):
@@ -400,7 +358,6 @@ class TestResearchResult:
             "citations",
             "gaps",
             "discovery_events",
-            "open_questions",
             "confidence",
             "confidence_factors",
             "cost_metadata",
@@ -408,10 +365,6 @@ class TestResearchResult:
         }
         assert set(data.keys()) == expected_keys
 
-        # OpenQuestion keys
-        oq_keys = {"question", "context", "priority", "source_locator"}
-        assert set(data["open_questions"][0].keys()) == oq_keys
-
         # Citation keys
         citation_keys = {
             "source",