medical-research-skills

Generates complete Mendelian randomization study designs from a user-provided exposure and outcome direction. Always use this skill whenever a user wants to design, plan, or build a Mendelian randomization study — even if phrased as "help me write a paper on X", "design an MR study for Y", or "I want to test whether A causally affects B using GWAS". Covers core two-sample MR design, optional bidirectional follow-up, optional multivariable MR, IV selection logic, ancestry alignment, harmonization, IVW as the default primary estimator, weighted median / MR-Egger / MR-PRESSO / leave-one-out sensitivity analyses, Steiger directionality, heterogeneity / pleiotropy checks, and explicit claim-boundary control. Always outputs four workload configs (Lite / Standard / Advanced / Publication+) with a recommended primary plan, stepwise workflow, method rationale, validation ladder, figure plan, minimal executable version, and strictly verified literature guidance with no fabricated references.

Screens research papers based on title/abstract and inclusion criteria, providing a structured Yes/No/Maybe decision. Use when you need to filter literature for meta-analysis or systematic reviews.

Generates the Methods section for a meta-analysis paper, including search strategy, screening, quality assessment, data extraction, and statistical analysis.

Generates a meta-analysis baseline characteristics section (text + table) from raw data. Supports Chinese and English. Use when the user provides baseline data and wants a formatted results section.

Generate Baujat plots for heterogeneity analysis. Identify studies that contribute most to the overall meta-analysis results and heterogeneity, helping discover potential outlier studies. Input meta-analysis data CSV, output Baujat plot PNG and contribution data CSV.

Access NIH Metabolomics Workbench (4,200+ studies) via REST API. Query metabolites, RefMet nomenclature, MS/NMR data, m/z search, study metadata for metabolomics and biomarker discovery.

Generates scientifically sound inclusion and exclusion criteria for Meta-Analysis based on a given title or keywords. Use when user wants to design eligibility criteria for a systematic review or meta-analysis.

Analyzes the feasibility of a proposed Meta-analysis topic by searching for existing Meta-analyses and Clinical Trials on PubMed/ClinicalTrials.gov. Use when you need to evaluate if a topic is viable for a new Meta-analysis.

Generate meta-analysis forest plots for binary classification data. Input is a CSV file containing study names, event counts and sample sizes for experimental and control groups. Output includes forest plot PNG and data table CSV.

Generate forest plots for meta-analysis of continuous data. Input a CSV file containing study names, means, standard deviations, and sample sizes for experimental and control groups. Output forest plot PNG and data table CSV.

Generate forest plots for meta-analysis of survival data. Input is a CSV file containing study names, HR and 95% confidence intervals, output forest plot PNG and data table CSV. Supports both R and Python scripts.

Generate Meta-analysis funnel plots and perform publication bias testing. Takes CSV file with Meta-analysis data as input, outputs funnel plot PNG, Egger test and Begg test results.

Analyze data with `metagenomic-krona-chart` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

Generates a first draft of a clinical meta-analysis paper. Input the research report (including Methods and Results sections), language, and title to automatically generate a complete paper draft including Abstract, Introduction, Discussion, and other sections, with automatic ...

Generates PI(E)COS structure (Population, Intervention, Comparator, Outcomes, Study Design) from Meta-analysis or study titles. Use when the user wants to extract these elements from a title.

Generates a PROSPERO-compliant Meta-analysis protocol based on Title and PICOS. Use when the user wants to write a protocol for a systematic review or meta-analysis.

Generate radial plots (Radial Plot/Galbraith Plot) for heterogeneity analysis. Visually assess heterogeneity across studies by displaying the relationship between standardized effect sizes and precision. Input: Meta-analysis data in CSV format; Output: Radial plot PNG and data CSV.

Analyzes forest plots for meta-analysis, generating detailed descriptions and formatting figure legends in Chinese or English. Use when the user wants to interpret a forest plot image, describe its statistical significance (heterogeneity, p-value), and format the output with s...

Generates a Meta-analysis results section description for funnel plots, including statistical tables (Egger's, Begg's, Trim & Fill) and figure legends. Supports English and Chinese outputs. Use when user provides a funnel plot image and statistics and wants a formatted report.

Generates the "Risk of Bias" results section for a meta-analysis based on assessment tables and statistics. Use when the user wants to draft the risk of bias analysis text from provided data tables.

Generates the "Results" section for meta-analysis sensitivity analysis based on statistical tables and titles. Use when the user wants to describe sensitivity analysis results or format sensitivity tables for a meta-analysis paper.

Draw ROB2 risk-of-bias plots, including a Traffic Light Plot and a Summary Bar Plot. Input is a CSV file with ROB2 assessments for each study; output are two PNG plot files.

Screen full-text papers against inclusion/exclusion criteria, with optional PubMed metadata check using PMID. Use when the user needs to evaluate a paper for a meta-analysis.