feat(synthesis): Lead/Provenance model + grounded leads + conjecture generator

- codex/synthesis.py: Lead/Provenance dataclasses, find_connections/gaps/improvements,
  propose_conjectures (status=unverified, quarantined in leads/conjectures/),
  write_leads (grounded→leads/grounded/, conjectures→leads/conjectures/ HARD invariant)
- codex/cli.py: synthesis leads/conjectures/report command group
- codex/config.py: F-13 settings (leads_dir, synthesis_llm_*, synthesis_top_k,
  synthesis_min_grounded_ratio, synthesis_gap_min_coverage)
- tests/synthesis/: 42 tests covering model, grounding, conjecture invariant, quarantine, CLI
- spike/: F-13 spike script + output (live run attempted)

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

tests/synthesis/conftest.py

@@ -0,0 +1,124 @@
+"""Shared synthesis fixtures — keep DB/LLM/embed fully mocked."""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any
+from unittest.mock import MagicMock
+
+import pytest
+
+# Shared corpus fixture used across the test suite.
+FIXTURE_CHUNKS: list[dict[str, Any]] = [
+    {
+        "id": 1,
+        "paper_id": "springborn-2008",
+        "ord": 16,
+        "content": (
+            "For an ideal tetrahedron with dihedral angles the hyperbolic volume is "
+            "V = L(gamma1) + L(gamma2) + L(gamma3). "
+            "The volume function V0 is strictly concave on the angle domain."
+        ),
+        "bibkey": "Springborn2008",
+    },
+    {
+        "id": 2,
+        "paper_id": "bps-2015",
+        "ord": 3,
+        "content": (
+            "A discrete conformal map is defined by logarithmic scale factors u_i "
+            "at each vertex such that the edge lengths satisfy a compatibility condition."
+        ),
+        "bibkey": "BobenkoPinkallSpringborn2015",
+    },
+    {
+        "id": 3,
+        "paper_id": "luo-2004",
+        "ord": 0,
+        "content": (
+            "The combinatorial Yamabe flow drives the edge lengths towards a target "
+            "curvature on a triangulated surface."
+        ),
+        "bibkey": "Luo2004",
+    },
+]
+
+
+class StubLLM:
+    """Deterministic mock LLM that returns a preset response."""
+
+    def __init__(self, response: str | list[str]) -> None:
+        if isinstance(response, str):
+            self._responses = [response]
+        else:
+            self._responses = list(response)
+        self._calls: list[tuple[str, str]] = []
+
+    def generate(self, prompt: str, model: str) -> str:
+        self._calls.append((prompt, model))
+        if not self._responses:
+            return ""
+        if len(self._responses) == 1:
+            return self._responses[0]
+        return self._responses.pop(0)
+
+    @property
+    def calls(self) -> list[tuple[str, str]]:
+        return list(self._calls)
+
+
+@pytest.fixture
+def stub_llm() -> StubLLM:
+    """Default stub returning empty string (override per test as needed)."""
+    return StubLLM("")
+
+
+@pytest.fixture
+def fixture_chunks() -> list[dict[str, Any]]:
+    return [dict(c) for c in FIXTURE_CHUNKS]
+
+
+@pytest.fixture
+def mock_retrieve(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Patch _retrieve_chunks to return deterministic fixture chunks (no DB)."""
+    monkeypatch.setattr(
+        "codex.synthesis._retrieve_chunks",
+        lambda queries, top_k: [dict(c) for c in FIXTURE_CHUNKS],
+    )
+
+
+@pytest.fixture
+def mock_paper_titles(monkeypatch: pytest.MonkeyPatch) -> None:
+    """Patch _list_paper_titles to return a deterministic three-paper corpus."""
+    monkeypatch.setattr(
+        "codex.synthesis._list_paper_titles",
+        lambda db_conn: [
+            ("Springborn2008", "A variational principle for weighted Delaunay triangulations"),
+            (
+                "BobenkoPinkallSpringborn2015",
+                "Discrete conformal maps and ideal hyperbolic polyhedra",
+            ),
+            ("Luo2004", "Combinatorial Yamabe Flow on Surfaces"),
+        ],
+    )
+
+
+@pytest.fixture
+def mock_settings(monkeypatch: pytest.MonkeyPatch, tmp_path: Path) -> Path:
+    """Settings stub pointing leads_dir at tmp_path/leads."""
+    from codex.config import Settings
+
+    leads_path = tmp_path / "leads"
+
+    mock = MagicMock(spec=Settings)
+    mock.leads_dir = str(leads_path)
+    mock.synthesis_llm_model = "test-model"
+    mock.synthesis_llm_url = None
+    mock.ollama_base_url = "http://localhost:11434"
+    mock.synthesis_top_k = 6
+    mock.synthesis_min_grounded_ratio = 0.5
+    mock.synthesis_gap_min_coverage = 2
+    mock.wiki_dir = str(tmp_path / "wiki")
+
+    monkeypatch.setattr("codex.synthesis.get_settings", lambda: mock)
+    return leads_path