schema-discovery

Name: schema-discovery
Availability: InStock
Author: Lytics

Map natural-language data concepts to profile schema fields with scoring.

4|1|Updated Apr 2, 2026

Search Tags:#schema #discovery #data-quality #profile #natural-language #field-mapping #field-types

Ready to run

npx skills add https://github.com/lytics/agent-skills --skill schema-discovery-lytics

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: schema-discovery
Source: https://github.com/lytics/agent-skills/tree/main/schema-discovery
Command: npx skills add https://github.com/lytics/agent-skills --skill schema-discovery-lytics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Fetch and interpret the profile schema to identify relevant fields for data mapping and validation.

Core Features & Use Cases

Schema discovery: list fields, types, and sample values from the profile schema.
Smart mapping: map natural-language descriptions to concrete fields across the user schema.
Support for downstream skills: feed field info into audience-builder, entity-lookup, and data-integration workflows.
Use case: map a description like "country and email" to actual schema fields for segmentation and targeting.

Quick Start

Find the profile field that matches a user description and return its name, type, and sample values.

Frequently Asked Questions about schema-discovery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I map natural-language descriptions to profile schema fields?▼

You can map natural-language descriptions to profile schema fields by applying field inventory, candidate scoring, and value distributions to select the best matches for concepts like country, email, or signup date.

What is schema discovery for data profiling?▼

Schema discovery for data profiling is the process of fetching and interpreting the profile schema to list fields, types, and sample values for relevant data mapping and validation.

How do I identify field types and sample values from a user table?▼

You identify field types and sample values by satisfying endpoints for listing fields, retrieving field info, and checking identity configuration to enable field selection and validation.

Can I use schema discovery to validate data quality for segmentation?▼

Yes, schema discovery validates data quality for segmentation by mapping described data concepts to actual profile schema fields and feeding the field info into audience-builder workflows.

What is the best way to select matching fields for common concepts like country and email?▼

The best way to select matching fields for common concepts like country and email is by applying candidate scoring and value distributions across the user table to map descriptions to concrete schema fields.