Tuning: the CI waits may be zero

The live review test sets ci_grace_s: 0, which the shared tuning parser
refused (every number had to be positive). A field now opts in to zero
with metadata {"zero": True}; ci_wait_s and ci_grace_s do.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk

nisse-core/src/nisse_core/config.py

@@ -81,13 +81,14 @@ def read_file(path: Path, errors: list[str]) -> dict[str, Any]:
     return loaded
 
 
-def positive(value: Any, kind: type) -> int | float | None:
+def positive(value: Any, kind: type, *, zero: bool = False) -> int | float | None:
+    """``value`` as ``kind`` if above 0 (or 0 itself, given ``zero``)."""
     # bool is an int in Python; `true` for a turn limit is a mistake.
     if isinstance(value, bool) or not isinstance(value, int | float):
         return None
     if kind is int and not float(value).is_integer():
         return None
-    if value <= 0:
+    if value < 0 or (value == 0 and not zero):
         return None
     return kind(value)
 
@@ -132,9 +133,13 @@ def parse_tuning(
             if spec is None:
                 errors.append(f"tuning.{name}.{key}: unknown setting")
                 continue
-            number = positive(value, float if spec.type in (float, "float") else int)
+            # A field with metadata {"zero": True} may also be 0 ("don't wait").
+            zero = bool(spec.metadata.get("zero"))
+            kind = float if spec.type in (float, "float") else int
+            number = positive(value, kind, zero=zero)
             if number is None:
-                errors.append(f"tuning.{name}.{key}: must be a positive number")
+                need = "zero or more" if zero else "a positive number"
+                errors.append(f"tuning.{name}.{key}: must be {need}")
                 continue
             values[key] = number
         sections[name] = cls(**values)

nisse-core/tests/test_shared_config.py

@@ -19,6 +19,7 @@ from nisse_core.config import (
 class Review:
     max_rounds: int = 3
     wait_s: float = 60.0
+    grace_s: float = field(default=5.0, metadata={"zero": True})
 
 
 @dataclass(frozen=True)
@@ -45,6 +46,17 @@ def test_an_agents_own_tuning_sections() -> None:
     ]
 
 
+def test_a_field_may_opt_in_to_zero() -> None:
+    errors: list[str] = []
+    tuning = parse_tuning({"review": {"grace_s": 0}}, Tuning, errors)
+    assert tuning.review.grace_s == 0 and errors == []
+    parse_tuning({"review": {"grace_s": -1, "wait_s": 0}}, Tuning, errors)
+    assert errors == [
+        "tuning.review.grace_s: must be zero or more",
+        "tuning.review.wait_s: must be a positive number",
+    ]
+
+
 def test_references_and_people() -> None:
     errors: list[str] = []
     env = {"TOKEN": "s3cret"}