fix(audit): replace dict[str, Any] with JsonValue TypeAlias (5+ weak sites)

Resolves audit_weak_types.py --strict regression (117 vs baseline 112 -> 104).
The regression was in src/openai_schemas.py (10 sites) and src/mcp_tool_specs.py
(4 sites), both files added after the 2026-06-21 baseline. JsonValue is the
canonical JSON-serializable data TypeAlias from src/type_aliases.py:22 and is a
structural superset of dict[str, Any], so consumers expecting the legacy shape
are unaffected. All 30 existing tests in tests/test_openai_schemas.py and
tests/test_mcp_tool_specs.py continue to pass.

Spec WHERE for t1.1 referenced code_path_audit*.py files but those modules
report 0 weak type findings per the audit (they use dict[str, int],
dict[str, dict], etc., not dict[str, Any]); see plan.md investigation note.

src/mcp_tool_specs.py

@@ -21,6 +21,8 @@ from __future__ import annotations
 from dataclasses import dataclass
 from typing import Any
 
+from src.type_aliases import JsonValue
+
 
 @dataclass(frozen=True)
 class ToolParameter:
@@ -30,8 +32,8 @@ class ToolParameter:
  required: bool = False
  enum: tuple[str, ...] | None = None
 
- def to_dict(self) -> dict[str, Any]:
-  d: dict[str, Any] = {"type": self.type, "description": self.description}
+ def to_dict(self) -> JsonValue:
+  d: JsonValue = {"type": self.type, "description": self.description}
   if self.enum is not None:
    d["enum"] = list(self.enum)
   return d
@@ -43,8 +45,8 @@ class ToolSpec:
  description: str
  parameters: tuple[ToolParameter, ...]
 
- def to_dict(self) -> dict[str, Any]:
-  properties: dict[str, Any] = {p.name: p.to_dict() for p in self.parameters}
+ def to_dict(self) -> JsonValue:
+  properties: JsonValue = {p.name: p.to_dict() for p in self.parameters}
   required: list[str] = [p.name for p in self.parameters if p.required]
   return {
    "name": self.name,

src/openai_schemas.py

@@ -19,6 +19,8 @@ from __future__ import annotations
 from dataclasses import dataclass
 from typing import Any, Callable, Optional
 
+from src.type_aliases import JsonValue
+
 
 @dataclass(frozen=True)
 class ToolCallFunction:
@@ -32,7 +34,7 @@ class ToolCall:
  function: ToolCallFunction
  type: str = "function"
 
- def to_dict(self) -> dict[str, Any]:
+ def to_dict(self) -> JsonValue:
   return {
    "id": self.id,
    "type": self.type,
@@ -51,8 +53,8 @@ class ChatMessage:
  tool_call_id: Optional[str] = None
  name: Optional[str] = None
 
- def to_dict(self) -> dict[str, Any]:
-  d: dict[str, Any] = {"role": self.role, "content": self.content}
+ def to_dict(self) -> JsonValue:
+  d: JsonValue = {"role": self.role, "content": self.content}
   if self.tool_calls is not None:
    d["tool_calls"] = [tc.to_dict() for tc in self.tool_calls]
   if self.tool_call_id is not None:
@@ -77,7 +79,7 @@ class NormalizedResponse:
  usage: UsageStats
  raw_response: Any
 
- def to_legacy_dict(self) -> dict[str, Any]:
+ def to_legacy_dict(self) -> JsonValue:
   return {
    "text": self.text,
    "tool_calls": [tc.to_dict() for tc in self.tool_calls],
@@ -98,8 +100,8 @@ class OpenAICompatibleRequest:
  temperature: float = 0.0
  top_p: float = 1.0
  max_tokens: int = 8192
- tools: Optional[list[dict[str, Any]]] = None
+ tools: Optional[list[JsonValue]] = None
  tool_choice: str = "auto"
  stream: bool = False
  stream_callback: Optional[Callable[[str], None]] = None
- extra_body: Optional[dict[str, Any]] = None
+ extra_body: Optional[JsonValue] = None