user-context

Load persisted Data Analytics source-routing preferences, onboarding state, and semantic-layer registry entries from local state files.

8|12|Updated Sep 19, 2025
One-click install
npx skills add https://github.com/xpert-ai/xpert-plugins --skill user-context-xpert-ai
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: user-context
Source: https://github.com/xpert-ai/xpert-plugins/tree/main/community/roles/data-analytics/skills/user-context
Command: npx skills add https://github.com/xpert-ai/xpert-plugins --skill user-context-xpert-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

Data Analytics workflows need persistent user preferences for data sources, onboarding progress, and semantic-layer definitions across sessions. Without durable state management, users must repeatedly configure sources, confirm onboarding steps, and redefine semantic layers for every new workflow.

Core Features & Use Cases

  • Source-Routing Preferences: Persists explicit future source choices so workflows automatically use the right connectors.
  • Onboarding State Management: Tracks setup progress, connector confirmation, and hero prompt history to guide new users.
  • Semantic-Layer Registry: Maintains discoverable pointers to source-backed semantic-layer skills for metrics and business definitions.
  • Script-Driven Preflight: Provides a deterministic JSON payload that downstream skills consume to load compact context before answering.

Quick Start

Use the user-context skill to load your saved Data Analytics source preferences, onboarding status, and semantic-layer registry before running any analysis workflow.

Frequently Asked Questions about user-context

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

FAQPage Schema
How do I persist data analytics source routing preferences across multiple sessions?

Data analytics source routing preferences are persisted across sessions by loading and managing durable choices from local state files. This ensures workflows automatically use the right connectors without requiring manual reconfiguration each time.

What is the best way to track onboarding state for data analytics workflows?

The best way to track onboarding state is by managing local state files that record setup progress, connector confirmation, and prompt history. This tracks setup steps to guide new users through the initial configuration process.

How does a semantic-layer registry work with data analytics plugins?

A semantic-layer registry works by maintaining discoverable pointers in local state files to source-backed semantic-layer skills. This provides downstream analytics workflows with accessible metrics and business definitions.

Can I use script-driven preflight to normalize user context before running analytics?

Yes, you can use script-driven preflight to generate a deterministic JSON payload that normalizes user context, connector confirmation, and onboarding progress. Downstream analytics skills consume this payload to load compact context before answering.

Do I need local state files for plugin initialization and context maintenance?

Yes, local state files are required for plugin initialization and context maintenance because they store the durable source-routing preferences, onboarding status, and semantic-layer registry entries necessary for persisted user choices.