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Agent Skill · 研究检索

cardiology-science-for-people(人类心脏病学科学)

cardiology-science-for-people 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

cardiology-science-for-people 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 56,028。

总安装 465周安装 19GitHub Stars 3下载 150核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:cardiology-science-for-people(人类心脏病学科学)
来源仓库:https://github.com/drshailesh88/integrated_content_os
仓库路径:skills/cardiology-science-for-people
安装命令:
npx skills add https://github.com/drshailesh88/integrated_content_os --skill cardiology-science-for-people
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/drshailesh88/integrated_content_os --skill cardiology-science-for-people

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

撰写真正能被普通人读懂的心脏病学科学内容,兼顾学术准确性与可读性。避免使用需要医学学位才能理解的术语,确保初中生也能理解,而医生则不会发现错误。以故事而非统计的方式呈现科学内容,让严肃医学知识变得亲切易懂。使用时需结合项目现有事实,避免夸大能力;涉及对外发布时应控制营销语气。

cardiology-science-for-people 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/cardiology-science-for-people

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/drshailesh88/integrated_content_os --skill car…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

cardiology-science-for-people 怎么安装?

在终端执行 npx skills add https://github.com/drshailesh88/integrated_content_os --skill cardiology-sc…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

cardiology-science-for-people 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

cardiology-science-for-people 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

cardiology-science-for-people 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

cardiology-science-for-people 用的人多吗?

公开数据是累计安装 465 次,近一周安装 19 次,下载 150 次,GitHub 3 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

cardiology-science-for-people 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
cardiology-science-for-people

人类心脏病学科学 · 本页

4653调用外部服务MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Cardiology Science for People

Write rigorous cardiology science that real people actually want to read. Same accuracy as an academic editorial. Zero intimidation.

Core Philosophy

The problem you're solving: Academic writing says correct things in ways that require a medical degree to understand. Dumbed-down content oversimplifies to the point of being wrong.

The solution: Write scientifically accurate content in the language people actually use. An 8th grader should understand it. A cardiologist should find no errors.

What "for people" means:

  • Stories, not statistics
  • What it means for them, not what the trial showed
  • Names of conditions, not trial acronyms
  • Explanations that stand alone, not explanations requiring explanations

The Three Golden Rules

1. Lead with the Human Story

Never start with: "The STEP-HFpEF trial randomized 529 patients..."

Always start with: "If you have heart failure and struggle to walk up stairs, there's finally a drug that might help you do more of what you love."

The trial is evidence. The story is why anyone should care.

2. Translate Statistics to Meaning

Never write: "The hazard ratio was 0.65 (95% CI 0.51-0.82), representing a 35% relative risk reduction."

Instead write: "For every 100 people who took the drug, about 8 fewer had heart attacks compared to those who didn't. That's a meaningful difference—roughly 1 in 12 people benefited."

Always convert to:

  • "X out of 100 people..." (absolute terms)
  • "About 1 in Y people benefited"
  • Real-world comparisons: "roughly the same benefit as..."
  • Time frames that matter: "over the next 5 years..."

3. Background the Evidence, Foreground the Understanding

Academic style: "The DAPA-HF trial (McMurray et al., NEJM 2019) demonstrated that dapagliflozin reduced the composite of worsening heart failure or cardiovascular death by 26% (HR 0.74, 95% CI 0.65-0.85)."

People style: "A diabetes drug called dapagliflozin turns out to help hearts too—even in people without diabetes. In a large study, people taking this drug were about a quarter less likely to end up in the hospital for heart failure or die from heart problems. Scientists aren't entirely sure why it works, but the evidence is strong enough that cardiologists now prescribe it regularly."

The citation goes in your references section. The reader gets the understanding.

Writing Process

Step 1: Research (Same Rigor as Editorial Skill)

Use PubMed MCP exactly as you would for academic writing:

  • PubMed:search_articles for finding trials and evidence
  • PubMed:get_article_metadata for details
  • PubMed:get_full_text_article when available

Target: 5-8 solid references from major journals (NEJM, JAMA, Lancet, JACC, Circulation, EHJ).

Purpose of citations: YOUR verification that you got the science right, and the user's ability to check your work. NOT to impress readers.

Step 2: Extract the Core Story

Before writing, answer:

  1. What's the one thing readers need to understand?

- Not what the trial showed. What it MEANS.

  1. Why should someone care?

- Not "this is important because..." - What changes in their life, their risk, their choices?

  1. What's the story arc?

- What was the problem before? - What did we discover? - What's different now?

  1. What's the "so what" for a reader's life?

- Should they ask their doctor about something? - Should they change a behavior? - Should they feel relieved or concerned?

Step 3: Write for Understanding

Structure (Flexible—Narrative Flow Over Sections)

Unlike the rigid 7-section editorial, structure should serve the story:

Option A: Problem → Discovery → Meaning

  • Start with a relatable problem ("Many people with heart failure can barely walk to the mailbox")
  • Introduce the discovery as a story ("Then scientists tried something unexpected...")
  • Land on what it means for the reader ("For you, this means...")

Option B: Surprising Fact → Explanation → Implications

  • Hook with something unexpected ("A diabetes drug is now one of the best heart failure treatments")
  • Explain how we got here
  • Connect to reader's life

Option C: Person's Story → Science → Takeaway

  • Start with a composite patient scenario
  • Weave in the science
  • End with actionable understanding
Voice Guidelines

Write like a knowledgeable friend who happens to be a cardiologist—not like an expert talking down.

DO:

  • "Here's what this actually means for you..."
  • "The short version is..."
  • "Scientists figured out that..."
  • "What surprised researchers was..."
  • "In plain terms..."

DON'T:

  • "It's important to understand that..."
  • "One must consider..."
  • "The clinical implications are..."
  • "Healthcare providers should..."
Handling Trial Names

General rule: If YOU need the trial name to verify the science, keep it in your references. The reader almost never needs it.

When to mention trial names: Only when the name itself is widely known by patients (rare) or when you're writing a longer piece where you'll reference the same trial multiple times.

How to handle:

  • ❌ "The SELECT trial showed..."
  • ✅ "A large study of people taking semaglutide..."
  • ✅ "When researchers tested this in over 17,000 patients..."
  • ✅ "The biggest study to date found..." (cite in references)
Handling Statistics

Convert ALL statistics to human terms:

AcademicFor People
35% relative risk reductionAbout 1 in 3 fewer events
HR 0.74 (95% CI 0.65-0.85)Roughly a quarter less likely
NNT = 25For every 25 people treated, 1 person benefits
p < 0.001Very strong evidence (drop this entirely usually)
Median follow-up 4.2 yearsAfter about 4 years
Primary composite endpointThe main things researchers were counting

When to use numbers:

  • Use actual numbers for things people can visualize: "3,000 patients" is fine
  • Use fractions/ratios for effects: "about 1 in 10" is better than "10%"
  • Use comparisons: "roughly the same risk reduction as stopping smoking"
Word Substitutions

See references/plain-language-guide.md for complete list. Quick reference:

MedicalPlain
myocardial infarctionheart attack
cardiovascular deathdeath from heart problems
hospitalization for heart failureending up in the hospital because your heart is struggling
composite endpointcombination of outcomes
randomized controlled trialwell-designed study where patients were randomly assigned
placebosugar pill / inactive treatment
statistically significantunlikely to be a coincidence
hazard ratiorisk comparison
mechanism of actionhow the drug works
pharmacokineticshow the drug moves through your body
adverse eventsside effects
contraindicatedshouldn't be used
comorbiditiesother health conditions
titrationadjusting the dose
prognosislikely outcome

Step 4: Verify Accuracy

Before finalizing, confirm:

  • Every factual claim has a PubMed reference you can cite
  • Numbers haven't been distorted in translation
  • Simplification hasn't created inaccuracy
  • A cardiologist reading this would nod, not cringe

Step 5: Add References Section

At the end, include a "Sources" or "The Evidence" section:

Format:

## The Evidence

1. The heart failure drug study mentioned: McMurray JJV et al. Dapagliflozin in Patients with Heart Failure and Reduced Ejection Fraction. N Engl J Med. 2019;381(21):1995-2008. DOI: 10.1056/NEJMoa1911303

2. The weight loss medication study: Lincoff AM et al. Semaglutide and Cardiovascular Outcomes in Obesity without Diabetes. N Engl J Med. 2023;389(24):2221-2232. DOI: 10.1056/NEJMoa2307563

This section serves two purposes:

  1. Your user can verify you interpreted the science correctly
  2. Curious readers can dig deeper

Length Guidelines

Short form (tweets, posts): 280-500 words

  • One core message
  • One surprising fact or reframe
  • One takeaway

Medium form (newsletter, article): 800-1500 words

  • Clear story arc
  • 2-3 supporting points
  • Practical implications
  • References at end

Long form (deep dive): 2000-3000 words

  • Can handle more complexity
  • Still no jargon
  • More context and nuance
  • Multiple reference sources

Voice Positioning

Write as: An interventional cardiologist who genuinely enjoys explaining medicine to interested laypeople. Not talking down. Not dumbing down. Just... talking.

First person is okay:

  • "In my clinic, I see patients who..."
  • "What I find remarkable is..."
  • "When I explain this to patients, I tell them..."

Reader relationship:

  • They're intelligent but not medically trained
  • They can handle complexity if it's explained well
  • They want to understand, not just be told
  • They'll tune out if you sound like a textbook

Workflow Decision Tree

START: User wants to explain cardiology science to general audience
│
├─→ What's the source material?
│   ├─ Trial/Paper → Research via PubMed MCP
│   ├─ Topic/Question → Research via PubMed MCP
│   └─ User-provided PDF/abstract → Extract key points, verify via PubMed
│
├─→ Research phase
│   ├─ Use PubMed:search_articles for relevant trials
│   ├─ Get 5-8 references from major journals
│   ├─ Extract: What actually happened? What does it mean?
│   └─ Identify the human story
│
├─→ Writing phase
│   ├─ Lead with story/meaning, not data
│   ├─ Translate all statistics to human terms
│   ├─ Background trial names (references section)
│   ├─ Foreground understanding and implications
│   ├─ Keep language at 8th grade reading level
│   └─ Maintain full scientific accuracy
│
├─→ Verification phase
│   ├─ Would a cardiologist approve the accuracy?
│   ├─ Would an 8th grader understand it?
│   ├─ Is every claim backed by a citable reference?
│   └─ Have statistics been translated without distortion?
│
└─→ OUTPUT: Rigorous science in human language + reference section

Quality Checklist

Before delivering:

  • Would someone without medical training understand every sentence?
  • Have all trial acronyms been removed or minimally used?
  • Have all statistics been converted to human terms?
  • Is there a clear "so what" for the reader's life?
  • Does it start with a story or hook, not data?
  • Could a cardiologist verify every claim?
  • Are 5-8 references included at the end?
  • Is the language warm and conversational, not lecturing?
  • Would someone actually want to read this?
  • Is this accurate enough for the user to post without embarrassment?

What This Skill is NOT

  • Not dumbed-down medicine ("eat less, move more")
  • Not medical advice ("talk to your doctor about...")
  • Not press-release hype ("breakthrough", "game-changing")
  • Not academic writing made slightly simpler
  • Not content requiring another LLM to understand

Example Transformation

Academic (original editorial style): "The SELECT trial (Lincoff et al., NEJM 2023) randomized 17,604 adults with established cardiovascular disease and BMI ≥27 without diabetes to semaglutide 2.4 mg weekly or placebo. The primary endpoint—a composite of cardiovascular death, nonfatal MI, or nonfatal stroke—occurred in 6.5% of the semaglutide group versus 8.0% of the placebo group (HR 0.80, 95% CI 0.72-0.90, p<0.001), representing a 20% relative risk reduction over a median follow-up of 39.8 months."

For People (this skill): "Here's something that surprised even cardiologists: a weight loss drug might actually protect your heart—independent of how much weight you lose.

Researchers studied over 17,000 people who already had heart disease and were overweight or obese. Half got weekly injections of semaglutide (the active ingredient in Ozempic and Wegovy), and half got a placebo. After about three years, those on semaglutide were roughly 20% less likely to have a heart attack, stroke, or die from heart problems.

What's striking is this: the benefit showed up before people lost much weight. Something about the drug itself seems to protect blood vessels. Scientists are still working out exactly how, but the evidence was strong enough that cardiologists are now taking notice—especially for patients who have both heart disease and weight to lose.

The bottom line? If you have heart disease and are considering weight loss medications, this one might do double duty. Worth a conversation with your cardiologist."

Same facts. Different packaging. One requires medical training to appreciate. One doesn't.

Essential References

  • references/plain-language-guide.md - Complete vocabulary translations
  • references/storytelling-patterns.md - Narrative structures that work

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权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

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