LLMs often produce free-form text, but many workflows need structured data. By providing explicit schemas and format instructions, prompts can elicit JSON, CSV rows or table layouts that integrate cleanly into pipelines.
Tools like output parsers and function-calling APIs validate structure before returning results. Clear examples and delimiters help the model follow the required schema with minimal post-processing.