Allow configurable context window for Claude Opus 4.6 (200K cap vs 1M model capability)

## Summary

GitHub Copilot CLI currently caps Claude Opus 4.6 at **200K tokens** of context, despite the model natively supporting **1M tokens**. This is an 80% reduction in available context that causes frequent automatic compaction (summarization) during deep technical sessions.

## Problem

When working on complex projects that involve reading large specs, multiple deliverables, and conducting multi-turn analysis, the 200K limit is hit quickly. Automatic compaction then discards context that was expensive to build (both in time and premium requests), forcing re-reads and losing nuance.

**Example session:** Reading a ~3,200-line protocol spec, ~56KB of research deliverables, a ~50KB wave plan, plus web searches and sub-agent outputs. This is well within the model's 1M capability but exceeds the 200K Copilot budget.

## Request

1. **Preferred:** Allow users to configure the context budget (e.g., `copilot --context-budget 500k` or a setting in `~/.copilot/config.json`). Users who need deep sessions can opt into higher token usage and accept the cost/latency tradeoff.
2. **Minimum:** Expose the current context budget in `/context` output alongside a note explaining the cap vs model capability, so users understand the constraint.

## Environment

- Copilot CLI version: 1.0.49-1
- Model: Claude Opus 4.6 (claude-opus-4.6)
- OS: Windows 11
- `/context` reports 200K token budget

## References

- Claude Opus 4.6 supports 1M tokens: https://www.anthropic.com/news/claude-opus-4-6
- Similar issue on Claude Code: https://github.com/anthropics/claude-code/issues/24208

Start at the `copilot --context-budget` entry point and the `/context` command, then inspect how `~/.copilot/config.json` is handled. Determine where the 200K budget is enforced and how configuration should interact with the model capability; done means users can set the budget or, at minimum, see the current cap and model capability in `/context`.

Scritto dal modello di indicizzazione a partire dal testo della issue.