user-profile-reader

Read user profiles from JSON and calculate content relevance scores.

21|3|Updated Dec 5, 2025

Search Tags:#tone #personalization #style #target #profile

Ready to run

npx skills add https://github.com/memorysaver/looplia-core --skill user-profile-reader

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: user-profile-reader
Source: https://github.com/memorysaver/looplia-core/tree/main/plugins/looplia-writer/skills/user-profile-reader
Command: npx skills add https://github.com/memorysaver/looplia-core --skill user-profile-reader

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Reads the user profile to tailor content relevance, tone, and style for downstream writing tasks.

Core Features & Use Cases

Reads ~/.looplia/user-profile.json
Calculates relevance score (score.relevanceToUser)
Feeds personalization data to other skills (e.g., idea-synthesis)

Quick Start

Use with the content-documenter and idea-synthesis to tailor outputs to the user.

Frequently Asked Questions about user-profile-reader

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

FAQPage Schema

How do I personalize content outputs based on user preferences and interests?▼

Personalize content by reading the user profile from ~/.looplia/user-profile.json, which contains topics with interest levels and style preferences. The Skill calculates a relevance score (0-1) that downstream tasks use to tailor tone, style, and topic focus to match user context.

What user profile data does the personalization workflow require?▼

The workflow requires a user-profile.json file containing userId, an array of topics with interestLevel values, and a style preference. This schema feeds into relevance scoring and context generation for content generation and recommendation tasks.

Can I use user profile data to filter content recommendations by relevance?▼

Yes. The Skill loads user profile topics and style, then produces a relevanceToUser score that other skills use to rank and filter recommendations. Downstream tasks like idea-synthesis consume this score to surface the most relevant content.

How do I integrate user profile personalization into content generation workflows?▼

Chain this Skill with content-documenter and idea-synthesis: read the user profile here to generate personalization context and relevance scores, then pass those outputs to downstream skills to tailor generated content tone, topics, and style to the user.

What happens if the user profile file is missing or incomplete?▼

The workflow requires ~/.looplia/user-profile.json with valid userId, topics array, and style fields. If the file is absent or lacks required schema fields, the Skill cannot calculate relevance scores or produce user context for downstream personalization tasks.

Does this approach work for both content generation and recommendation systems?▼

Yes. The relevanceToUser score and user-context output support personalization across content generation, recommendations, and summaries. The reproducible workflow consumes the same user-profile.json schema for any downstream task requiring personalized outputs.