docs: custom output extraction

[jleguina]

In deep agent workflows, each sub‐agent automatically performs an LLM step to summarize its tool calls before returning to its parent. This leads to:

1. Excessive latency: every nested agent invokes the LLM, compounding delays.
2. Loss of raw tool data: summaries may strip out details the top‐level agent needs.

We discovered that Agent.as_tool(...) already accepts an (undocumented) custom_output_extractor parameter. By providing a callback, a parent agent can override what the sub‐agent returns e.g. hand back raw tool outputs or a custom slice so that only the final agent does summarization.

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This PR adds a “Custom output extraction” section to the Markdown docs under “Agents as tools,” with a minimal code example.