Let copilot ask before it starts expensive exploration

### Describe the bug

In the light of https://github.blog/news-insights/company-news/github-copilot-is-moving-to-usage-based-billing I observed the token usage and counts and got surprised of how much tokens are sometimes consumed for some relative simple tasks, especially for the input tokens.

I try to find out why but due to
- https://github.com/github/copilot-cli/issues/3011

its very hard to guess, I just found that often it _seems_ the case that copilot is hitting a wall and then trying *too hard* to fix it itself *instead of asking the user*.

One example was where compilation failed because it used the wrong compile command. This resulted in an unfortunate and long cycle where it tried to use a complete other tool (e.g. `javac` instead of maven, writing an own python script instead of using a prepared shell script or java tool) wanted to search the whole maven local repo or even decompiling java classes to learn method signatures (where it could have downloaded the source would be probably more effective) then needed multiple iterations until if finally found something. This not only wastes tokens, but also lead to poor results (e.g. even if copilot was able to compile the actual CI build might fail because required dependencies where not added) and takes a lot of time. I noticed similar where copilot was not able to execute a test and then began to bring up a whole own infrastructure to execute the single unit test where it would probably be easier to just run the regular full test suite.

Instead of trying to hard in such case it would be **extremely helpful** if in such case copilot would *just ask* how to proceed with maybe an option to just try as hard as possible, skip the step or getting further assistance.

### Affected version

_No response_

### Steps to reproduce the behavior

_No response_

### Expected behavior

_No response_

### Additional context

_No response_

未指定任何文件、测试或入口点。首先重现一次会触发扩展探索的编译或测试失败尝试，然后追踪 Copilot 如何决定继续还是询问用户。完成标准应包括一个清晰的提示，其中提供继续、跳过或请求指导的选项，并覆盖报告中的探索案例。

由索引模型根据 Issue 内容生成。