Dynamic Nested Attributes

What it does

This skill allows AI agents to process and manipulate data structures with deeply nested attributes. It can extract specific values from complex, hierarchical datasets, transform these structures based on instructions, and generate new structured outputs. The agent can navigate through multiple levels of nesting using path-like specifications.

When to use it

• Data Extraction: Pulling key information (e.g., a product's warranty details) from a complex JSON object representing a catalog.
• Configuration Management: Modifying deeply nested settings within a configuration file format like YAML or TOML.
• Report Generation: Creating summaries and reports by extracting data from nested records in a database export.
• Data Transformation: Restructuring data from one nested format to another, for example converting between different API response structures.

Key capabilities

• Nested attribute access using path-like specifications (e.g., data.customer.address.city).
• Value extraction from deeply nested objects.
• Transformation of nested data based on provided rules or instructions.
• Generation of new structured outputs with modified or extracted data.

Example prompts

• "Extract the 'street' attribute from the customer address in this JSON: [JSON data]"
• "Modify the 'discount_percentage' within the 'promotion' object at path 'order.items[2].promotion'."
• “Create a new JSON structure containing only the ‘name’ and ‘price’ attributes, nested under a top-level key called ‘products’, from this complex data: [JSON data]"

Tips & gotchas

The agent requires clear and precise paths to navigate nested attributes. Incorrect path specifications will result in errors or unexpected behavior. Be mindful of data types when transforming values; incorrect type conversions can lead to corrupted data.