clinical-research

Identify and flag issues in clinical manuscript study design and reporting.

1|Updated Apr 23, 2026

Search Tags:#reporting #epidemiology #study-design #manuscripts #bias-assessment #clinical-review #safety-claims

Ready to run

npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill clinical-research

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: clinical-research
Source: https://github.com/Avaivartika/jiaoleaf-ai/tree/main/extension/skills/science/clinical-research
Command: npx skills add https://github.com/Avaivartika/jiaoleaf-ai --skill clinical-research

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Review clinical, biomedical, epidemiology, and health AI manuscripts for study design, reporting, bias, outcomes, and safety claims.

Core Features & Use Cases

Identify study type, population, inclusion/exclusion criteria, endpoints, and follow-up.
Check confounding, missing data, calibration, external validation, and subgroup analysis.
For predictive models, check leakage, temporal validation, decision threshold, and clinical utility.
Provide structured feedback and cautious language to improve reporting.

Quick Start

Review the attached manuscript for methodological quality and reporting.

Frequently Asked Questions about clinical-research

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I review a clinical manuscript for study design and bias?▼

To review a clinical manuscript for bias, check confounding factors, missing data handling, calibration, external validation, and subgroup analysis. This identifies methodological flaws in clinical, biomedical, and epidemiology study designs, providing structured feedback and cautious language for transparent reporting improvements.

Can I assess predictive model leakage and clinical utility in health AI manuscripts?▼

Yes, you can assess predictive model leakage and clinical utility in health AI manuscripts. The process checks for data leakage, temporal validation, decision threshold, and clinical utility to flag methodological issues and provide structured recommendations for cautious, transparent interpretation of outcomes.

Does this work for varied clinical study designs like RCTs and cohort studies?▼

Yes, this works for varied clinical study designs including RCTs, cohort studies, and diagnostic studies. It applies relevant reporting standards to evaluate study type, population, inclusion criteria, endpoints, and follow-up, flagging issues in reporting quality, bias, outcomes, and safety claims across different study designs.

What is the best way to check reporting quality and safety claims in biomedical manuscripts?▼

The best way to check reporting quality and safety claims in biomedical manuscripts is to systematically identify study type, population, endpoints, and follow-up. Evaluate confounding, missing data, and subgroup analysis to provide structured recommendations and cautious wording for transparent interpretation of outcomes.

How do I get structured feedback and wording for improving clinical manuscript reporting?▼

To get structured feedback and wording for improving clinical manuscript reporting, review the manuscript for methodological quality. Identify issues in study design, reporting quality, bias, outcomes, and safety claims to receive structured recommendations and cautious language that supports transparent interpretation.