Implement cloud-planner-proxy: AI planner routes through Cloud API

Implements all 19 tasks of the cloud-planner-proxy OpenSpec change:

- Cloud API: cloud.planner_config (CloudPlannerConfig, load/build helpers)
  reusing runtime.tool_calling_client provider clients (no new dependency
  needed -- device-cloud-platform already depends on device-agent-runtime).
- Cloud API: new host-scoped POST /internal/v1/hosts/{host_id}/planner/decide
  internal endpoint, reusing existing bearer auth; logs only metadata
  (host id, tool name, latency, error class), never prompt/screenshot
  content.
- Host Agent: new AI_PLANNER_TRANSPORT config (direct default | cloud) and
  host_agent/cloud_planner_client.py::CloudProxyToolCallingClient, a
  synchronous ToolCallingClient implementation (structural, not importing
  runtime) that calls the new endpoint via its own httpx.Client -- avoids
  bridging the async HostAgentClient across the worker-thread boundary
  that AIPlanner.plan() runs in (asyncio.to_thread in lease.py).
- Host Agent wiring: create_execution_factories()/_host_agent_planner()
  select the cloud-proxy client only when AI_PLANNER_TRANSPORT=cloud;
  direct/unset transport is unchanged (still the default).
- Tests: 22 new tests across Cloud API config, the new endpoint, the new
  client, and transport-selection wiring; full non-integration suite
  (492 tests) passes with no regressions.
- Docs: docs/CLOUD_DEPLOYMENT.md documents the cloud transport, its
  trade-offs, and the credential split between Host Agent and Cloud API.

proposal.md/design.md were corrected during implementation to reflect two
findings: no new anthropic/openai dependency is actually needed, and
CloudProxyToolCallingClient uses its own sync httpx.Client rather than a
new HostAgentClient method, per the thread-boundary reasoning above.

packages/cloud-platform/cloud/internal_api/models.py

@@ -96,3 +96,28 @@ class TerminalResultResponse(BaseModel):
 class StaleLeaseConflict(BaseModel):
     code: Literal["stale_lease"] = "stale_lease"
     detail: str
+
+
+class PlannerToolSpecModel(BaseModel):
+    name: str = Field(min_length=1)
+    description: str = ""
+    parameters: dict[str, Any] = Field(default_factory=dict)
+
+
+class PlannerDecisionRequest(BaseModel):
+    host_id: str = Field(min_length=1)
+    system_prompt: str
+    user_prompt: str
+    screenshot_base64: str | None = None
+    tools: list[PlannerToolSpecModel] = Field(default_factory=list)
+    timeout_seconds: float = Field(default=30.0, gt=0, le=120)
+
+
+class PlannerDecisionResponse(BaseModel):
+    tool_name: str
+    arguments: dict[str, Any] = Field(default_factory=dict)
+
+
+class PlannerDecisionError(BaseModel):
+    code: Literal["planner_unavailable"] = "planner_unavailable"
+    detail: str