Structured Output Extractor

What it does

The Structured Output Extractor skill allows AI agents to parse unstructured text and extract data into a structured format, like JSON or CSV. It can identify key pieces of information within the text and organize them according to predefined schemas. This is useful for automating tasks that require extracting specific details from documents or conversations.

When to use it

• Summarizing meeting transcripts: Extract action items, decisions made, and attendees from lengthy meeting notes.
• Processing customer feedback: Categorize and quantify sentiment and feature requests from open-ended survey responses.
• Extracting data from invoices: Automatically pull out invoice numbers, dates, amounts due, and vendor information.
• Analyzing product reviews: Identify common themes and specific features mentioned in a large set of online reviews.

Key capabilities

• Parses unstructured text.
• Extracts data into structured formats (JSON, CSV).
• Identifies key pieces of information.
• Organizes extracted data according to schemas.

Example prompts

• "Extract the product name and price from this customer review: 'I love this widget! It's amazing and only costs $29.99.'"
• "Can you extract the date, amount, and vendor from this invoice text?"
• "From this meeting transcript, please provide a JSON object containing all action items assigned to John."

Tips & gotchas

The accuracy of extraction depends heavily on the clarity and consistency of the input text. Providing clear instructions about the desired output format (e.g., specifying the exact keys for a JSON schema) will improve results.