htlin222

htlin222 / zh-ebn-report-skill

Public

台灣護理實證報告（N1–N4 升等）教練 skill。Install: npx skills add htlin222/zh-ebn-report-skill

15
6
100% credibility
Found Apr 26, 2026 at 15 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

An AI-powered coach that guides Taiwanese nurses through creating compliant evidence-based nursing reports for professional advancement, handling literature search, appraisal, synthesis, and drafting.

How It Works

1
🏥 Discover the nursing report helper

You hear about this AI coach from nursing colleagues, designed to help Taiwanese nurses create professional evidence-based reports for career advancement.

2
💻 Set it up in your AI chat

Add the helper to your favorite AI assistant like Claude with a simple one-click install, no tech skills needed.

3
📝 Start with your topic idea

Tell it a rough idea like 'delirium care' or 'pressure ulcers', and pick your report type like reading summary or case study.

4
🔍 Let AI guide the full process

The coach refines your question, finds relevant studies, checks their quality, summarizes findings, and drafts each section while you approve key steps.

5
✅ Review and finalize sections

Check the draft sections for tone, format, and fit, making tweaks as needed before the final polish.

📄 Get your ready-to-submit report

Receive a complete, formatted document with all required disclosures, ready for review and advancement submission, saving hours of work.

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Star Growth

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AI-Generated Review

What is zh-ebn-report-skill?

This Python-based skill, installed via `npx skills add htlin222/zh-ebn-report-skill`, automates generating evidence-based nursing (EBN) reports for Taiwan's N1-N4 advancement exams. Feed it a vague topic like "pressure ulcer prevention," and it runs the full 5A process—topic refinement, PICO setup, multi-DB search strategies, CASP appraisals, synthesis, and section drafting—spitting out a Quarto-rendered DOCX draft compliant with Taiwan Nursing Association rules, complete with AI disclosure templates. Run it as a Claude Code skill for chat-driven workflow or standalone CLI for scripted automation.

Why is it gaining traction?

It crushes the drudgery of manual lit reviews and formatting for niche EBN reports, bundling knowledge bases, search tools (PubMed, Scopus, CrossRef validation), and guards against common pitfalls like vague language or invalid DOIs. Developers in healthcare love the zero-config skill protocol integration—no API keys for basic use—and the HITL checkpoints that keep humans in the loop for ethics. At 15 stars, it's early but hooks users with ready-to-submit drafts that pass society audits.

Who should use this?

Taiwanese nurses grinding N1-N4 promo reports, especially EBR reading reports or case analyses under tight deadlines. Perfect for those juggling shifts while formatting PICO searches, CASP checklists, and APA refs—add it to your skills toolkit if you're in clinical evidence workflows.

Verdict

Grab it if you're the target user; the Python pipeline delivers polished EBN reports fast, with strong docs and tests despite 1.0% credibility and low stars signaling early maturity. Polish your own audits before submission, but it's a time-saver worth the npx add.

(178 words)

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