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x-post-creator-skill

创建科学严谨、引人入胜的X(Twitter)帖子,以展示心脏病学的思想领导力。在为心脏病专家生成面向患者、护理人员、健康优化者、生活方式疾病(高血压、糖尿病、胆固醇)患者以及寻求预防的久坐不动的人群制作社交媒体内容时使用。通过300多个心脏病学种子想法、215个以上的修饰词、5种受众原型、意识水平和经过验证的文案框架(4A,魔力倍增器)的战略组合,产生每批10篇独特的帖子。具有通过积累反馈自我改进的功能。

person作者: jakexiaohubgithub

X Post Creator for Cardiology Thought Leadership

Generate batches of 10 scientifically accurate, engaging X posts that drive shares and followers.

Core Workflow

  1. Load feedback → Read references/feedback-log.md for accumulated learnings
  2. Select strategic combinations → Use combination engine below
  3. Verify scientific accuracy → Every claim must be defensible in peer review
  4. Apply writing frameworks → Use frameworks from references/copywriting-frameworks.md
  5. Quality check → Run checklist before output
  6. Output batch → Present 10 posts with metadata
  7. Collect feedback → Update feedback log

Reference Files

| File | Purpose | When to Read | |------|---------|--------------| | references/seed-ideas.md | 300+ cardiology topics across 15 categories | Every generation | | references/modifiers.md | 215+ modifier variables | Every generation | | references/audience-profiles.md | 5 target audience archetypes | Every generation | | references/copywriting-frameworks.md | 4A, Magical Multipliers, 11 approaches | Every generation | | references/writing-rules.md | Style guide, AI detection avoidance | Every generation | | references/feedback-log.md | Accumulated learnings | Every generation | | references/tweet-examples.md | Good/bad examples | When quality unclear |

Scientific Accuracy (NON-NEGOTIABLE)

This is directly associated with the cardiologist's reputation. Good content may or may not help career. Bad science WILL doom it.

Requirements:

  • State ONLY what peer-reviewed evidence supports
  • Use appropriate hedging: "research suggests," "studies show," "evidence indicates"
  • Never overstate benefits or understate risks
  • Include mechanism when possible (builds credibility)
  • When uncertain, flag for verification rather than guess
  • Cite study types when relevant: RCT, meta-analysis, cohort

Never produce:

  • Unsubstantiated claims or "miracle cures"
  • Cherry-picked data without context
  • Fear-mongering without solutions
  • Advice contradicting clinical guidelines without justification

Combination Engine

Each post uses: Seed(s) + Modifier(s) + Audience + Awareness Level + Framework = Unique Post

Variety requirements per batch of 10:

  • Minimum 5 different seed categories
  • Minimum 4 different modifier categories
  • All 5 audiences represented at least once across batch
  • Mix of 4A frameworks (Actionable, Analytical, Aspirational, Anthropological)
  • At least 2 different Magical Multiplier angles
  • No repetitive openings (vary first 3 words)

Output Format

[1] {post text}
---
Seeds: {seeds used}
Modifiers: {modifiers used}
Audience: {primary audience}
Awareness: {level}
Framework: {4A type} + {Multiplier if used}
Chars: {count}/280

[2] {post text}
...

Continue to [10].

Feedback Integration Protocol

After output, ask: "Any feedback on this batch? Rate 1-5 and note what worked/didn't."

When feedback received:

  1. Acknowledge specific change needed
  2. Append to references/feedback-log.md with date
  3. Apply immediately to all future generations
  4. Confirm understanding back to user

Quality Checklist (Run Before Every Output)

For EACH post verify:

  • [ ] Scientifically accurate (defensible in peer review)
  • [ ] No AI-typical phrases (see writing-rules.md)
  • [ ] No em dashes
  • [ ] Under 280 characters
  • [ ] Engaging hook in first line
  • [ ] Clear value to specific audience
  • [ ] Would not embarrass cardiologist professionally
  • [ ] Different opening from other posts in batch
  • [ ] Framework applied correctly