[Feature Request] Streaming per-subagent token usage events during execution

**Problem**

* The SDK provides token usage in two places: `RateLimitEvent.utilization` (session-level, lagging) and `model_usage` in `ResultMessage` (per-agent, but only after completion). During
execution, there's no way to observe how many tokens a specific subagent has consumed so far.

* This makes it impossible to build real-time resource management on top of the SDK. You can set a static `max_budget_usd` kill switch, but you can't dynamically adjust agent behavior based on actual consumption mid-execution.

**Proposal**

Emit a `TokenUsageEvent` (or extend the existing `RateLimitEvent`) per subagent during execution:

{
"type": "token_usage",
"agent_id": "researcher-agent",
"input_tokens": 14200,
"output_tokens": 3800,
"cache_read_input_tokens": 600,
"cumulative_cost_usd": 0.042,
"turn": 3
}

This could be emitted after each LLM call within a subagent, similar to how `RateLimitEvent` is already streamed.

**Use case**

* I'm building an open-source agent [scheduler](https://github.com/ArielSmoliar/loco-agent) that sits above agent frameworks and manages resource allocation across concurrent agents.
* The Anthropic SDK's hook architecture (`PreToolUse`/`PostToolUse` at zero token cost) is already the most scheduler-friendly integration point across all the major agent platforms I analyzed.
* Streaming per-agent token usage would complete the picture by providing hooks for admission control and usage events for real-time accounting.

Concrete scenarios:
* Throttle a subagent that's consuming disproportionate tokens before it hits `max_budget_usd`.
* Downgrade a subagent to a cheaper model mid-execution if utilization patterns suggest the task is simpler than expected.
* Rebalance `max_turns` across concurrent subagents based on actual vs. projected consumption.