medical-research-skills

Assess translational gaps between preclinical models and human diseases.

Designs a translational blueprint for moving a biomedical finding toward diagnosis, prognosis, treatment response prediction, patient stratification, or therapeutic development, with explicit translational milestones, validation thresholds, and feasibility-sensitive route framing.

Generate concise (typically 1–4 pages) patient-centered medical treatment plans in LaTeX/PDF when a clinician needs an actionable plan with SMART goals, evidence-based interventions, monitoring, and HIPAA-aware documentation.

Designs studies for predicting treatment response or resistance in biomedical and clinical research. Always use this skill when the user needs a treatment-response or resistance prediction study blueprint rather than a prognostic biomarker protocol, diagnostic test design, causal treatment-effect estimation, or a completed manuscript. Focus on responder definition, treatment context, baseline comparability, feature integration strategy, model development logic, validation architecture, and interpretation boundaries. Do not invent response rates, cohort size, assay readiness, regimen uniformity, literature support, or validation access.

Generates complete tumor immune-infiltration-guided bulk-transcriptome diagnostic biomarker and machine-learning research designs from a user-provided cancer type and study direction. Always use this skill whenever a user wants to design, plan, or build a tumor bioinformatics study centered on differential expression, immune infiltration estimation, immune-linked module discovery, consensus feature selection, diagnostic modeling, nomogram construction, clinical association, and optional prognostic extension or validation. Covers five study patterns (immune-cell-first diagnostic workflow, immune-module-to-biomarker workflow, consensus-ML biomarker workflow, diagnostic-plus-prognostic hybrid workflow, translational validation workflow) and always outputs four workload configs (Lite / Standard / Advanced / Publication+) with recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, reference literature pack, and self-critical risk review.

Generates complete two-sample Mendelian randomization research designs from a user-provided outcome, exposure or exposure family, and robustness direction. Use when a study centers on summary-statistics causal inference with instrument selection, harmonization, IVW-primary estimation, complementary estimators, sensitivity analyses, optional multivariable upgrades, and conservative evidence interpretation. Covers five study patterns and always outputs Lite / Standard / Advanced / Publication+ with a recommended primary plan, stepwise workflow, figure plan, validation hierarchy, minimal executable version, publication upgrade path, and strictly verified literature retrieval.

Generates complete two-sample Mendelian randomization (MR) research designs from a user-provided research direction. Use when users want to design, plan, or build a study using two-sample MR to test causal relationships. Triggers:"design a two-sample MR study", "build a publishable MR paper", "test whether this biomarker causally affects this disease", "generate Lite/Standard/Advanced MR plans", "screen multiple exposures with MR", "bidirectional MR design", "causal inference using GWAS summary statistics", or "I want to study X and Y using MR". Always outputs four workload configurations (Lite / Standard / Advanced / Publication+) with a recommended primary plan, step-by-step workflow, figure plan, validation strategy, minimal executable version, and publication upgrade path.

Use when performing sample-level dimensionality reduction and visualization on abundance or OTU-style matrices with a companion group file, generating UMAP and/or t-SNE coordinates and plots for group separation assessment. NOT for: differential expression testing, single-cell workflows requiring dedicated embeddings pipelines, or analyses without a sample grouping file.

Direct REST API access to UniProt for protein search, entry retrieval, and identifier mapping; use when you need programmatic UniProtKB queries or cross-database ID conversion.

Use when running prognostic survival analysis on a clinical cohort with time-to-event data to estimate univariate and multivariable Cox proportional hazards models, export result tables, and generate forest plots. NOT for: nomogram construction, calibration curves, time-dependent ROC analysis, or model training/feature selection beyond the built-in univariate screening rule.

Extracts concrete unmet clinical needs from guidelines, reviews, real-world studies, and clinical-practice evidence. Use this skill when a user wants to turn broad medical research value into specific clinical pain points such as weak early detection, poor risk stratification, treatment-response heterogeneity, monitoring gaps, diagnostic delay, undertreatment, overtreatment, or implementation failure. Always ground unmet-need claims in retrieved evidence and distinguish true care gaps from generic statements of importance.

Mine unstructured clinical text from MIMIC-IV to extract diagnostic logic.

Convert complex Venn diagrams with more than 4 sets to clearer Upset.

Generate USMLE Step 1/2 style clinical cases with patient history, physical.

Access USPTO data (Patent Search, PEDS, TSDR, assignments) when you need to query patents/trademarks and retrieve prosecution or status information programmatically.

Designs internal, external, temporal, and functional validation strategies at the protocol stage for medical research studies.

Query and annotate gene variants from ClinVar and dbSNP databases. \n\.

Integrate REVEL, CADD, PolyPhen scores to predict variant pathogenicity.

Fix garbled text in PDF/SVG vector graphics caused by font encoding issues, making files editable in AI tools. Supports batch processing and JSON export for manual correction.

Venue-specific LaTeX templates, formatting requirements, and submission guidelines for journals, conferences, posters, and grants—use when a target venue imposes strict layout, page limits, anonymization, or agency compliance rules.

Simulate standardized patient encounters for medical training, supporting OSCE-style history-taking practice, communication skills rehearsal, and educational debriefing.

Generates detailed text descriptions of medical images and charts for.

Analyze data with `volcano-plot-labeler` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.

Generate R/Python code for volcano plots from DEG (Differentially Expressed Genes) analysis results. Triggered when user needs visualization of gene expression data, p-value vs fold-change scatter plots, publication-ready figures for bioinformatics analysis.

Guide for disposing specific chemical wastes into the correct colored waste containers, with safety precautions and regulatory compliance notes.