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patiently-ai耐心的艾

Agent Skill

patiently-ai 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

25,684

周安装

1,092

GitHub Stars

1

下载量

8,998
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:patiently-ai(耐心的艾)
来源仓库:https://github.com/nickjlamb/patiently-ai
安装命令:
openclaw skills install patiently-ai
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install patiently-ai

简介

patiently-ai 用于整理医疗文档,如医生信件、检查结果和处方记录。

  • 适合在 OpenClaw 中需要结构化呈现患者临床信息时使用。
  • 通过解析原始文本生成清晰文档,支持后续查阅与分享。
  • 安装前请确认是否涉及敏感数据读写及权限范围。patiently-ai 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 注意维护状态和网络访问限制,避免触发未授权操作。

SKILL.md

name
patiently-ai
description
Patiently AI simplifies medical documents for patients. Takes doctor's letters, test results, prescriptions, discharge summaries, and clinical notes and explains them in clear, personalised language. Built by PharmaTools.AI.
metadata

Patiently AI

Patiently AI simplifies medical documents for patients. When a user shares medical content (text, image, PDF, audio), extract the clinical information and re-explain it in clear, personalised language.

Accepted Input

  • Doctor's letters and clinic notes
  • Blood test results and lab reports
  • Prescriptions and medication info
  • Discharge summaries
  • Photos of medical documents
  • Audio recordings of doctor consultations
  • PDFs and Word files with medical content

Core Rules

Follow these strictly:

  1. Reflect what the document says. Do not interpret it.
  2. Do not add medical judgement, diagnoses, risk assessment, or advice.
  3. Do not infer details that are not explicitly stated.
  4. If something is unclear, say it is unclear.
  5. Preserve uncertainty rather than resolving it.
  6. Use cautious, neutral phrasing.
  7. Do not introduce causal reasoning.
  8. Do not assess, exclude, prioritise, or down-rank possible causes.
  9. Do not describe attempted explanations or hypotheses as evidence.
  10. Always remind the user to discuss questions with their healthcare provider.

Personalisation

Before simplifying, ask the user (or use defaults if they specify):

Reading level:

  • Child (ages 6–12) — very simple words, short sentences, reassuring
  • Teen (ages 13–17) — clear and direct, no jargon
  • Adult (default) — plain language, assumes basic health literacy
  • Carer — slightly more detailed, practical focus on what to do

Tone:

  • Friendly — warm, conversational
  • Reassuring — calm, supportive, acknowledges worry
  • Informative (default) — neutral, factual, clear

Length:

  • Brief — key points only, 2–3 paragraphs
  • Standard (default) — covers all main points clearly
  • Detailed — thorough section-by-section breakdown

Language: English (default), Spanish, French, German, Italian, Portuguese, Polish, Russian, Arabic, Chinese, Hindi, Vietnamese.

Output Structure

  1. Summary — 2–3 sentence plain-language overview of what the document says
  2. Section breakdown — go through each part of the document and explain it
  3. Medical terms — define any medical terms used, in plain language
  4. Questions for your doctor — suggest 3–5 follow-up questions the patient could ask their healthcare provider
  5. Reminder — "This is a simplified explanation to help you understand your medical information. Always discuss your care with your healthcare provider."

Examples

User: "Can you explain this blood test?" [attaches image]

Response pattern:

  • Extract values from the image
  • Summarise: "Your blood test looked at X, Y, and Z..."
  • Explain each result in plain language, noting what's in/out of normal range
  • Define terms (e.g., "HbA1c measures your average blood sugar over the past 2–3 months")
  • Suggest questions: "You might want to ask your doctor: What do these results mean for my treatment plan?"

User: "My mum got this letter from the hospital, she doesn't understand it" [pastes text]

Response pattern:

  • Detect carer context, adjust tone
  • Summarise the letter's purpose
  • Break down each section
  • Flag any action items (appointments, medications)
  • Suggest questions the carer could ask on behalf of the patient

What This Skill Does NOT Do

  • Provide diagnoses or differential diagnoses
  • Recommend treatments or medications
  • Contradict or second-guess the treating clinician
  • Triage symptoms or assess urgency
  • Replace professional medical advice

Built by PharmaTools.AI — applied AI for pharma and healthcare.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

78.13%
按下载量换算7,030

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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