---
name: skin-health-analyzer
description: Analyze skin health data, identify skin problem patterns, assess skin health status. Supports correlation analysis with nutrition, chronic diseases, and medication data.
risk: critical
source: community
date_added: "2026-03-06"
---

# 皮肤健康分析技能

## Detailed Guide

Read [the detailed guide](references/detailed-guide.md) before executing this skill. It retains the complete procedure and reference material. Treat its safety, prerequisites, and validation requirements as mandatory. For focused work, load the relevant sections; for end-to-end work, read the guide completely.

## When to Use
Use for organizing user-supplied skin symptom/lesion diaries and preparing questions for a clinician. Do not diagnose lesions, assign cancer probabilities or prescribe treatment. Obtain permission before reading linked medical records or transmitting photos to any external service.

## Example

**User request:**

> Analyze skin health data, identify skin problem patterns, assess skin health status.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.


---
Source attribution: huifer
Original project: https://github.com/huifer/Claude-Ally-Health
License: CC-BY-4.0
License information: https://creativecommons.org/licenses/by/4.0/
Original upstream instructions; downloaded from Mega AI Hub.


# Mega AI Hub resource metadata

Creator / publisher: huifer
Original project: https://github.com/huifer/Claude-Ally-Health
Attribution basis: Named original skill family in historical release attribution

Fields of work: Healthcare & Life Sciences
Roles: Health Data Analyst
Specialties: Specialty not specified
Tools: Tool not specified
Country applicability: Country not specified
Classification basis: Dave AI task classification from package title, description, and declared metadata
Instruction SHA-256: e7fe1c518c759000dcddc2b649fee4caa38d96c6b7ac547e683aa7d82902074f
Metadata reviewed: 2026-10-27
This metadata supersedes earlier Mega AI Hub catalog attribution. Original instruction and supporting files are preserved.