skincare-learn

Teaches evidence-based skincare through a 13-module adaptive curriculum with progress tracking.

17|1|Updated Jun 16, 2026
One-click install
npx skills add https://github.com/swaylq/sijiao-skill --skill skincare-learn-swaylq
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skincare-learn
Source: https://github.com/swaylq/sijiao-skill/tree/main/prototypes/skincare-learn
Command: npx skills add https://github.com/swaylq/sijiao-skill --skill skincare-learn-swaylq

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Skincare information is dominated by marketing noise, making it hard to distinguish evidence-based basics from overhyped products or conditions that actually need a dermatologist. This Skill acts as a stateful personal tutor that teaches scientific skincare from zero, remembers where you left off, and adapts exercises to your level. ## Core Features & Use Cases - Structured 13-module curriculum: Progresses from novice (skin barrier, skin type, the core three of cleanse/moisturize/sunscreen) through advanced beginner (routines, actives, patch testing) to competent (targeted concerns, barrier repair, knowing when to see a dermatologist). - Adaptive coaching with learner state: Reads and updates learner-state.json to track mastery, weak spots, misconceptions, spaced-repetition queues, and streaks, then generates exercises matched to your level. - Honest safety boundaries: Explicitly flags what AI cannot do — it cannot see your skin, recommends patch testing for new actives, and directs skin diseases or suspicious moles (ABCDE rule) to a dermatologist. - Use Case: A learner overwhelmed by product marketing asks to learn skincare; the tutor diagnoses their skin type and goals, builds a minimal routine, reviews their ingredient choices for conflicts, and schedules spaced reviews of sunscreen dosage and active-ingredient rules. ## Quick Start Ask the tutor to teach you scientific skincare from scratch and diagnose your skin type and current routine.

Frequently Asked Questions about skincare-learn

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

FAQPage Schema
How do I learn skincare from scratch with an AI tutor?▼

Start by telling the tutor your skin type, main concerns, and current products. It places you at the right module, teaches one topic at a time, asks you to write your own routine or ingredient plan, and checks your logic against evidence-based sources.

What does the skincare curriculum cover?▼

The 13 modules cover skin barrier basics, skin-type self-assessment, the core three (cleansing, moisturizing, sunscreen), building minimal routines, active ingredients like retinoids and vitamin C, patch testing, barrier repair, targeted concerns, and when to see a dermatologist.

Can an AI skincare coach replace a dermatologist?▼

No. This Skill explicitly states it is not medical advice and cannot see your skin. Moderate-to-severe acne, rosacea, eczema, melasma, and suspicious or changing moles require an in-person dermatologist visit, and the curriculum teaches you to recognize those boundaries.

How does the tutor track my learning progress?▼

It maintains a learner-state JSON file recording per-module mastery scores, weak spots, misconceptions, exercise results, a spaced-repetition queue, and streaks. Each session reads this file to resume where you left off and target weak areas.

Why does the tutor emphasize patch testing new actives?▼

Active ingredients like retinoids, acids, and vitamin C carry irritation and allergy risks. The curriculum requires a 48-hour patch test behind the ear or on the inner arm before facial use, and introduces only one new active at a time at low frequency.