神經科病歷助手

自動將神經科門診病歷文本結構化，提取主訴、病史、檢查、診斷及治療建議。

Security Scan

The skill's requirements and instructions are coherent with its stated purpose (structuring neurology outpatient notes); it requests no credentials, installs nothing, and contains no code — but it lacks any guidance about handling sensitive patient data.

Purpose & Capability

Name and description match the runtime instructions: the SKILL.md only asks the agent to accept clinical note text and output structured fields (chief complaint, HPI, exam, assessment, plan). There are no unexpected binaries, env vars, or config paths required.

Instruction Scope

Instructions stay within the stated purpose and reference only the input note and desired structured output. However, the SKILL.md does not state any policy about storage, logging, or transmission of patient-identifiable data (PHI), nor does it specify clinical validation or safety checks. This is a privacy and clinical-safety omission rather than a coherence/integrity issue.

Install Mechanism

No install spec and no code files are present, so nothing is written to disk or fetched at install time. This minimizes supply-chain risk.

Credentials

The skill declares no environment variables, credentials, or config paths. There are no requests for unrelated secrets or high-privilege access that would be disproportionate to the stated function.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request permanent inclusion or modification of other skills. Autonomous model invocation is allowed by platform default but is not a unique privilege of this skill.

Assessment

This skill appears internally consistent and low-risk from a code/credential perspective because it is instruction-only and asks for no installs or secrets. The primary concern is privacy and clinical safety: do not feed real patient-identifiable information (PHI) unless you have guarantees about data handling, retention, and compliance (e.g., HIPAA/GDPR). Ask the publisher or platform: where is input sent (which model/provider), is any logging or storage performed, how long are inputs retained, and has the output been clinically validated? If you must evaluate, test with synthetic or de-identified notes first and confirm legal/regulatory compliance before using on real patient data.

神經科病歷結構化助手

將門診病歷輸入，自動輸出結構化總結，包括診斷同建議。

使用方式

1. 輸入門診病歷原始文字
2. AI會自動提取：
   • 主訴 (Chief Complaint)
   • 病史 (History of Present Illness)
   • 檢查發現 (Physical Exam Findings)
   • 診斷 (Assessment)
   • 治療建議 (Plan)

範例輸入

患者男性，65歲，主訴右側肢體無力3小時。既往有高血壓、糖尿病病史。查體：血壓180/100mmHg，右上肢肌力2級，右下肢肌力3級...

輸出示例

• 結構化病歷摘要
• 可能的診斷
• 進一步檢查建議
• 治療方案建議

適用對象

• 神經內科醫生
• 門診護士
• 醫學生成AI愛好者