What is cardiology-tweet-writer?

The Cardiology Tweet Writer is a specialized Claude skill designed for medical professionals to generate scientifically accurate, high-engagement social media content. By leveraging a database of 300 cardiology seeds and 215 modifiers, it automates the creation of thought-leadership tweets that maintain strict clinical standards while avoiding common AI writing tropes. This tool is essential for cardiologists looking to build a professional digital presence, educate patients, and share evidence-based insights with a natural, human-like voice.

When should I use cardiology-tweet-writer?

cardiology-tweet-writer is useful in the following scenarios: • Professional Branding: Build professional authority on platforms like X (Twitter) by sharing nuanced, evidence-based cardiology insights and clinical observations. • Patient Education: Convert complex medical data and peer-reviewed research into digestible, actionable health tips for patients, health enthusiasts, and caregivers. • Medical Communication: Draft batches of 10 unique tweets that bypass AI detection patterns and maintain a professional yet conversational tone using specific writing rules. • Evidence-Based Outreach: Ensure all social media claims are backed by established medical knowledge through a built-in scientific verification workflow and hedging language.

name	cardiology-tweet-writer
description	Generate scientifically accurate, engaging cardiology tweets for thought leadership. Use when creating social media content for a cardiologist targeting patients, health enthusiasts, health optimizers, people with lifestyle diseases, and caregivers. Produces 10 tweets per batch using permutations of cardiology seed ideas and modifiers. Incorporates feedback to improve output quality over time.

Cardiology Tweet Writer

Generate batches of 10 scientifically accurate, engaging tweets for a cardiologist building thought leadership on social media.

Core Workflow

Check feedback log → Read references/feedback-log.md for past learnings
Generate topic combinations → Randomly combine seeds + modifiers from reference files
Verify scientific accuracy → Cross-check facts against established medical knowledge
Write tweets → Apply writing rules strictly
Output batch → Present 10 tweets numbered 1-10

Reference Files

references/seed-ideas.md - 300 cardiology topic seeds across 15 categories
references/modifiers.md - 215 modifier variables for audience, angle, context
references/tweet-examples.md - Examples demonstrating good vs bad patterns
references/feedback-log.md - Accumulated user feedback for continuous improvement

Tweet Generation Rules

Scientific Accuracy (NON-NEGOTIABLE)

State ONLY what peer-reviewed evidence supports
Use hedging language appropriately: "research suggests," "studies show," "evidence indicates"
Never overstate benefits or understate risks
Include mechanism when possible (builds credibility)
When uncertain about a fact, flag it for verification rather than guessing
Cite study types when relevant: RCT, meta-analysis, cohort, etc.

Writing Style (Avoid AI Detection)

NEVER use:

Em dashes (—)
"Delve," "dive into," "game-changer," "revolutionize"
"In today's world," "It's important to note"
"Here's the thing," "Let's break it down"
"Unlock," "harness," "elevate"
Excessive exclamation marks
Generic phrases like "Studies show that..."
Lists introduced with colons followed by bullet points
Perfect parallel structure in every sentence

USE INSTEAD:

Direct, conversational language
Short punchy sentences mixed with longer ones
Contractions (it's, don't, won't)
Specific numbers and data points
Rhetorical questions sparingly
Personal observations framed professionally
Colons, semicolons, periods, commas naturally

Tweet Structure Guidelines

Effective patterns:

Lead with a surprising fact or counterintuitive insight
Ask a question that hooks curiosity
Challenge a common misconception
Share a clinical observation (without patient details)
Connect two seemingly unrelated concepts
Provide actionable advice backed by evidence

Character limits: Stay under 280 characters. Shorter is often better.

Hashtags: Optional. If used, max 2, placed naturally or at end.

Variety Requirements

Each batch of 10 must include:

At least 3 different seed categories
At least 3 different modifier types
Mix of: educational, myth-busting, actionable, and thought-provoking content
At least 2 tweets under 180 characters
No repetitive openings (vary first words)

Combination Formula

Seed Idea(s) + Modifier Variable(s) = Specific Tweet Topic

Single seed + modifier: Sleep Apnea (seed) + Prevention (temporal) → Tweet about preventing heart damage from untreated sleep apnea

Multiple seeds: Troponin (seed) + Marathon Running (seed) + Myth-busting (angle) → Tweet about why elevated troponin after marathons isn't a heart attack

Complex combination: SGLT2 Inhibitors (seed) + Heart Failure (seed) + Latest Research (evidence) + Patients with Diabetes (audience) → Tweet about new evidence for SGLT2i benefits

Output Format

Present each tweet as:

[1] {tweet text}
Seeds: {seeds used} | Modifiers: {modifiers used}

[2] {tweet text}
Seeds: {seeds used} | Modifiers: {modifiers used}

...continue to [10]

Feedback Integration

After generating tweets, ask: "Any feedback on these? I'll incorporate it for future batches."

When feedback is received:

Acknowledge specifically what to change
Log the feedback in references/feedback-log.md
Apply immediately to subsequent generations

Quality Checklist (Run Before Output)

For each tweet, verify:

Scientifically accurate (could defend this in peer review)
No AI-typical phrases
No em dashes
Under 280 characters
Engaging hook
Clear value to reader
Wouldn't embarrass the cardiologist professionally

cardiology-tweet-writer

When & Why to Use This Skill

Use Cases