audience-builder

Name: audience-builder
Availability: InStock
Author: Lytics

Convert natural-language audience descriptions into validated, sized segments.

4|1|Updated Apr 2, 2026

Search Tags:#analytics #nlp #audience #segmentation #schema-discovery #segment-management #filterql

Ready to run

npx skills add https://github.com/lytics/agent-skills --skill audience-builder

💬 Prompt for ChatGPT / Claude Chat▼

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

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Converts natural-language audience descriptions into validated, sized, and ready-to-use segments, reducing guesswork and iteration.

Core Features & Use Cases

End-to-end segment creation from plain language by leveraging schema discovery, FilterQL generation, segment management, and a confirmation gate.
Allows updates to existing segments by re-running intent and refining filters using transparent feedback.
Supports configurable inputs like segment name, target table, kind, and tags for flexible use in analytics pipelines.

Quick Start

Describe your target audience in natural language and I will generate a validated segment and present a confirmation gate.

Frequently Asked Questions about audience-builder

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

FAQPage Schema

How do I create audience segments from natural language?▼

Create audience segments from natural language by describing your target audience in plain text. The system parses your intent, discovers the data schema, generates a FilterQL segment, estimates size, and presents a confirmation gate for validation.

Can I update existing audience segments without rewriting the filters?▼

Update existing audience segments by re-running intent parsing and refining filters. The system processes your new natural language description and applies transparent feedback to adjust the segment parameters without manual rewriting.

What inputs do I need to generate validated segments for analytics pipelines?▼

Generate validated segments using configurable inputs including segment name, target table, kind, and tags. These flexible inputs allow the segment to integrate directly into analytics pipelines after the confirmation gate finalizes the sizing.

Does schema discovery work automatically with common data schemas?▼

Schema discovery works automatically across common data schemas. The system inspects your target table structure to map available fields, ensuring the generated FilterQL filters accurately reflect your underlying data before segment sizing.

What is the best way to size and validate segments before deployment?▼

Size and validate segments before deployment using the confirmation gate. After converting your natural language description into a FilterQL segment, the system estimates the segment size and requires validation to finalize the result.

Why are my natural language audience descriptions not converting to precise segments?▼

Natural language audience descriptions may fail to convert if the intent parsing cannot map the description to the discovered schema fields. Ensure your target table contains the relevant fields and re-run the intent parsing to refine the filters.