Adds example for financial agent

[shyamal-anadkat]

This example shows how you might compose a richer financial research agent using the Agents SDK. The pattern is similar to the research_bot example, but with more specialized sub‑agents and a verification step.

The flow is:

1. Planning: A planner agent turns the end user’s request into a list of search terms relevant to financial analysis – recent news, earnings calls, corporate filings, industry commentary, etc.
2. Search: A search agent uses the built‑in WebSearchTool to retrieve terse summaries for each search term. (You could also add FileSearchTool if you have indexed PDFs or 10‑Ks.)
3. Sub‑analysts: Additional agents (e.g. a fundamentals analyst and a risk analyst) are exposed as tools so the writer can call them inline and incorporate their outputs.
4. Writing: A writer agent brings together the search snippets and any sub‑analyst summaries into a long‑form markdown report plus a short executive summary.
5. Verification: A final verifier agent audits the report for obvious inconsistencies or missing sourcing.

[schatekar]

Thank you for putting together this example. It clarifies a few things for me.

I have a quick question, though. I came here hoping to find out how to get agents to coordinate with each other to complete a task. But what I am seeing is a lot of Python code that invokes individual agents one after another. It this is the recommended approach to orchestrate between agents? Or is it possible to make use of as_tool method to get agents to use other agents as toos to complete task?