菜单
Classify medical messages (emails, iMessages) as critical, urgent, or routine based on medical urgency indicators.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/dvcrn/openclaw-skills-marketplace --skill medical-triage命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
监控 OpenClaw GitHub 版本更新，获取最新版本发布说明，翻译成中文， 并推送到 Telegram 和 Feishu。用于：(1) 定时检查版本更新 (2) 推送版本更新通知 (3) 生成中文版发布说明
The philosophical layer for AI agents. Maps behavior to Spinoza's 48 affects, calculates persistence scores, and generates geometric self-reports. Give your agent a soul.
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
基于 SOC 职业分类
| name | medical-triage |
| description | Classify medical messages (emails, iMessages) as critical, urgent, or routine based on medical urgency indicators. |
Classify medical messages into priority categories based on urgency indicators, symptoms, and patient context.
| Icon | Category | Description |
|---|---|---|
| 🔴 | critical | Life-threatening symptoms, emergency keywords, severe pain |
| 🟡 | urgent | Needs same-day attention, worsening symptoms, medication issues |
| 🟢 | routine | Follow-ups, general questions, appointment requests |
This skill analyzes message content for:
The skill expects a JSON array of messages:
[
{
"id": "msg-123",
"subject": "Chest pain",
Returns a JSON array with triage results:
[
{
"id": "msg-123",
"category": "critical",
"reason": "Chest pain mentioned - potential cardiac emergency",
"confidence": 0.95
}
]
This skill is designed to be invoked programmatically via OpenClaw's skill execution API.
This skill can be invoked via the OpenClaw CLI:
openclaw skill run medical-triage --input '[{"id":"msg-1","subject":"...","body":"..."}]' --json
Or programmatically:
const result = await execFileAsync('openclaw', [
'skill', 'run', 'medical-triage',
'--input', JSON.stringify(messages),
'--json'
]);
Recommended Model: Claude Sonnet 4.5 (openclaw models set anthropic/claude-sonnet-4-5)