feat(agents): pydantic output schemas (Pick/AgentOutput/RunManifest) + tests

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016DvdRZkyCy9NJpHYDdPqmS

tests/test_schemas.py

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+"""Phase-0 gate: the output contract validates and rejects garbage."""
+
+from __future__ import annotations
+
+from datetime import datetime, timezone
+
+import pytest
+from pydantic import ValidationError
+
+from agents.schemas import AgentOutput, AgentStatus, Direction, Pick, RunManifest
+
+
+def _pick(**kw) -> Pick:
+    base = dict(ticker="nvda", conviction=0.8, thesis="momentum", requested_weight_pct=0.05)
+    base.update(kw)
+    return Pick(**base)
+
+
+def test_pick_valid_and_ticker_uppercased():
+    p = _pick()
+    assert p.ticker == "NVDA"
+    assert p.direction == Direction.LONG
+
+
+def test_conviction_out_of_range_rejected():
+    with pytest.raises(ValidationError):
+        _pick(conviction=1.5)
+
+
+def test_weight_must_be_positive_fraction():
+    with pytest.raises(ValidationError):
+        _pick(requested_weight_pct=0.0)
+    with pytest.raises(ValidationError):
+        _pick(requested_weight_pct=1.5)
+
+
+def test_stop_take_pct_must_be_fraction():
+    with pytest.raises(ValidationError):
+        _pick(stop_loss_pct=7.0)  # 700% — clearly a mistake
+    assert _pick(stop_loss_pct=0.07).stop_loss_pct == 0.07
+
+
+def test_long_absolute_levels_ordering_enforced():
+    with pytest.raises(ValidationError):
+        _pick(entry_type="limit", limit_price=100.0, stop_price=105.0)  # stop above entry
+    with pytest.raises(ValidationError):
+        _pick(entry_type="limit", limit_price=100.0, take_price=95.0)  # take below entry
+    ok = _pick(entry_type="limit", limit_price=100.0, stop_price=93.0, take_price=120.0)
+    assert ok.limit_price == 100.0
+
+
+def test_agent_output_roundtrip():
+    out = AgentOutput(
+        agent_name="Nova",
+        persona_id="nova",
+        started_at=datetime.now(timezone.utc),
+        status=AgentStatus.COMPLETE,
+        picks=[_pick(), _pick(ticker="amd", conviction=0.6)],
+    )
+    restored = AgentOutput.model_validate_json(out.model_dump_json())
+    assert restored.agent_name == "Nova"
+    assert [p.ticker for p in restored.picks] == ["NVDA", "AMD"]
+
+
+def test_run_manifest_minimal():
+    m = RunManifest(
+        run_id="r1",
+        trade_date="2026-07-01",
+        model="gpt-oss-20b",
+        started_at=datetime.now(timezone.utc),
+    )
+    assert m.status == "running"
+    assert m.agents == []