user-context

Manage Data Analytics plugin routing preferences and semantic-layer registry in user-context.md.

488|76|Updated Jun 2, 2026
One-click install
npx skills add https://github.com/openai/role-specific-plugins --skill user-context-openai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: user-context
Source: https://github.com/openai/role-specific-plugins/tree/main/plugins/data-analytics/skills/user-context
Command: npx skills add https://github.com/openai/role-specific-plugins --skill user-context-openai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Load and manage the Data Analytics plugin's durable source-routing preferences, onboarding logic, setup progress, and semantic-layer registry.

Core Features & Use Cases

  • Stores explicit future source-routing choices per core data category and semantic-layer pointers to guide upcoming analytics reads.
  • Tracks onboarding progress and semantic-layer setup state to ensure consistent workflow context across sessions.
  • Provides a lightweight, query-friendly surface for preflight reads and setup gating without becoming a long-term memory store.

Quick Start

Save a first routing preference under a core category (for example, Prefer: Databricks for structured_data) and begin the onboarding flow.

Frequently Asked Questions about user-context

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

FAQPage Schema
How do I manage durable source-routing preferences for data analytics workflows?

Durable source-routing preferences are managed by saving explicit routing choices per core data category, which shapes future analytics reads and guides upcoming semantic-layer queries across sessions.

What is semantic-layer registry management and when do I need it for onboarding?

Semantic-layer registry management tracks onboarding progress and setup state to ensure consistent workflow context, applying during initial setup, maintenance, and direct analytic workflows requiring routing context.

How do I configure preflight reads and onboarding gates for a semantic layer?

Preflight reads and onboarding gates are configured using bundled Python scripts that read and write state files, enforcing setup progress and orchestrating query-friendly preflight checks before analysis.

Does the Data Analytics plugin support tracking onboarding state across sessions?

Yes, the plugin tracks onboarding progress and semantic-layer setup state by writing to durable state files, ensuring consistent workflow context and setup gating across multiple sessions.

What are the limitations of using a lightweight preflight read for semantic-layer setup?

The preflight read surface provides query-friendly setup gating without becoming a long-term memory store, meaning it is designed for lightweight routing checks rather than persistent analytical data retention.

What's the best way to start onboarding and save my first data routing preference?

Begin the onboarding flow by saving a first routing preference under a core data category, such as preferring a specific source for structured data, to initialize the semantic-layer context.