wildcatter turns a natural-language question into a standalone Python script that answers it. You ask something like "revenue per comma in the CEO letter for every Fortune 50 company" — an LLM decomposes it into a plan, writes a Python script that fetches real data (SEC filings, FRED, Wikipedia, Yahoo Finance, web scraping), runs it, validates the output with auto-generated tests, and saves the result as a reusable "rig." Rigs re-run without the LLM. If something breaks (API changed, site restructured), the system calls the LLM to fix the code automatically. You can also set up triggers to re-run on a schedule or when a condition fires. The output is a structured table you can export directly to excel or via MCP
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