Extends a mechanistic or association-level biomedical finding into a staged validation pathway that moves from descriptive evidence toward stronger functional support, mechanistic specificity, and clinical relevance. Use this skill when a user has a pathway, biomarker, cell-state, target, mechanism, or association finding and needs to decide what should be validated next, in what order, and which evidence layers are necessary versus optional. Do not default to maximal validation stacks. Build a structured validation ladder with a primary route, stronger upgrade route, and optional extensions.

Converts an audited medical research gap into a complete, structured, gap-traceable study design. Always use this skill whenever a user already has one or more candidate research gaps and wants to transform them into an executable biomedical research plan rather than re-run broad topic ideation. Covers six gap-to-design patterns (evidence-completion, mechanism-resolution, cell-state/context-mapping, translation-bridge, causality-upgrade, population/stage-specific) and always outputs one recommended primary protocol, a gap-to-design dependency map, step-by-step workflow, figure plan, validation strategy, minimal executable version, publication upgrade path, and verified design-support literature rules. Never fabricate references. Preserve claim-evidence discipline and do not replace a topic-specific gap with a generic workflow.

Designs complete research plans that integrate clinical variables with multi-omics data from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a study that combines clinical variables with transcriptomics, proteomics, metabolomics, epigenomics, or related omics layers for mechanism interpretation, biomarker development, risk stratification, treatment-response analysis, or translational use. It should define the clinical use case, alignment across data layers, feature-reduction and fusion logic, modeling route, mechanism-interpretation layer, validation ladder, and four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, accession numbers, sample counts, metadata completeness, platform coverage, literature references, PMIDs, DOIs, or validation status. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.

Generates complete NHANES-style cross-sectional epidemiology + retrospective clinical validation research designs from a user-provided disease and biomarker direction. Always use this skill whenever a user wants to design, plan, or build a population-level biomarker association study using NHANES or similar survey datasets, especially when the article logic includes disease definition, biomarker formula derivation, multivariable logistic regression, restricted cubic spline analysis, subgroup stability testing, and a secondary hospital-based retrospective validation cohort. Covers five study patterns (cross-sectional association, dose-response / RCS, subgroup-stability, NHANES + retrospective validation, preliminary screening-performance) 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...

Compares multiple study-route options for the same biomedical research question and recommends one primary plan, while explicitly explaining why alternative routes are secondary, premature, weaker, or dependency-heavy. Always use this skill when the user already has a reasonably defined question but is unsure which main study route should anchor the project. Focus on plan comparison, route selection, dependency awareness, and primary-plan justification rather than full protocol drafting.

Designs discovery, modeling, and validation workflows for prognostic biomarkers in biomedical and clinical research. Always use this skill when the user needs a prognostic biomarker study blueprint rather than a diagnostic test protocol, predictive biomarker design, treatment recommendation, or a completed manuscript. Focus on endpoint family, follow-up horizon, time scale, candidate marker strategy, model-building logic, risk stratification framework, and internal/external validation requirements. Do not invent cohort size, event rate, assay readiness, literature support, or validation access.

Designs complete single-cell research plans from a user-provided biomedical direction. Always use this skill whenever a user wants to design, scope, or structure a single-cell study — including disease-focused, mechanism-focused, biomarker-focused, translational, perturbation-inspired, or validation-aware projects. It should define the research question, choose the best-fit study pattern, recommend sample grouping logic, suggest reference datasets as examples only, specify the core analysis modules, propose a validation ladder, and output four workload configurations (Lite / Standard / Advanced / Publication+). Never fabricate datasets, sample metadata, accession numbers, cohort availability, cell-type labels, external validation resources, or literature references. Always include the mandatory Dataset Disclaimer immediately before any workflow section that mentions datasets or public resources.

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.

Creates academic-poster writing packages for LaTeX using beamerposter, tikzposter, or baposter. Use when a user needs poster-ready section copy, figure plans, captions, and package-specific layout decisions for conference or thesis posters.

Data structure for annotated matrices in single-cell analysis; use when reading/writing .h5ad (or zarr) and exchanging data with the scverse ecosystem.

Unified Python access to 40+ bioinformatics web services; use when you need to query multiple databases (e.g., UniProt/KEGG/ChEMBL/Reactome) with one consistent API in a single workflow, especially for cross-database analysis and identifier mapping.

ETE (Environment for Tree Exploration) toolkit for phylogenetic and hierarchical tree analysis; use it when you need to parse/manipulate Newick/NHX trees, detect duplication/speciation events, integrate NCBI taxonomy, and render publication-quality figures.

Statistical analysis and reporting for experimental datasets; use when you need to interpret experimental results, test significance (t-tests/ANOVA), or generate reproducible reports.

Parse Flow Cytometry Standard (FCS) files v2.0–3.1 and extract events/metadata for preprocessing workflows (e.g., when you need NumPy arrays, channel info, or CSV/DataFrame export from cytometry files).

A high-performance Rust toolkit (with Python bindings and a CLI) for genomic interval analysis; use it when you need fast overlap queries, coverage track generation, genomic tokenization for ML, reference sequence verification, or fragment processing.

Process, clean, and compare mass spectrometry (MS/MS) spectra with Matchms; use when you need reproducible spectral filtering and similarity scoring for metabolomics workflows.

A low-level plotting library for comprehensive customization. Use when fine-grained control over every plot element is needed, creating new types of charts, or integrating into specific scientific workflows. Can export to PNG/PDF/SVG for publication. For quick statistical charts, use seaborn; for interactive charts, use plotly; for journal-style, publication-ready multi-panel charts, use scientific-visualization.

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.

Generates Meta-Analysis research titles based on user keywords, utilizing PubMed search results if available, or creative generation otherwise. Use when the user wants to brainstorm or generate titles for a meta-analysis, specifically starting from keywords or a topic.

Predict neoantigens that may be recognized by the immune system based.

Differential gene expression analysis for bulk RNA-seq count matrices using a DESeq2-like workflow in Python; use when you need Wald tests, FDR correction, and optional LFC shrinkage for condition/batch/covariate designs.

Comprehensive tool for computational mass spectrometry using PyOpenMS; use when you need to read/write MS formats (mzML/mzXML/MGF), run signal processing (smoothing/peak picking), detect isotope features, or perform peptide identification in proteomics/metabolomics workflows.

Genomic file toolkit. For reading/writing SAM/BAM/CRAM alignment files, VCF/BCF variant files, FASTA/FASTQ sequences, extracting regions, calculating coverage, suitable for NGS data processing pipelines.

Automated bias assessment for diagnostic accuracy studies using QUADAS-C criteria. Requires full text input.

Automates Risk of Bias 2 (ROB2) assessment for RCT papers by analyzing text against specific domains and synthesizing a report. Use when you need to assess the quality of a clinical trial paper or evaluate risk of bias.

Guided statistical analysis for test selection, assumption checks, power analysis, and APA-style reporting. Use when you need to choose an appropriate statistical test for your data and produce publication-ready results (including effect sizes and diagnostics).

Determines the appropriate Risk of Bias assessment scale for a medical study based on its design (RCT, Cohort, etc.), using PubMed metadata lookup or text analysis. Use when the user wants to know which quality assessment tool to use for a specific paper (given PMID or abstract).

Kaplan-Meier survival analysis tool for clinical and biological research. Generates publication-ready survival curves with statistical tests.

Intelligent medical abbreviation disambiguation tool that resolves ambiguous acronyms using clinical context, specialty-specific knowledge, and document-level semantic analysis.

Search, retrieve metadata, and download PDFs for bioRxiv preprints; use when you need to discover biology preprints by keywords/authors/date ranges and programmatically fetch their details.

Programmatic access to the BRENDA enzyme database via the SOAP API; use when you need kinetic constants (Km, kcat, Vmax), reaction equations, enzyme properties (pH/temperature optima, stability), or enzyme discovery by EC/substrate/product.

Access ChEA3 and Harmonizome ChEA data for transcription factor enrichment analysis and metadata retrieval. Use when the user needs to perform ChEA3 enrichment analysis on a gene set, get metadata about the ChEA dataset, or retrieve information about a specific transcription factor (attribute).

Batch extracts and verifies structured information (PMID, title, abstract, methodology, results, etc.) from clinical research literature using PMIDs. Use when the user wants to extract details from specific PMIDs.

Access the ENCODE Project REST API to search for and retrieve biological data (biosamples, experiments, etc.). Use this skill when the user needs to query ENCODE data, search by keywords, or retrieve specific objects by accession ID.

Query the NCBI Gene database via E-utilities and the NCBI Datasets API; use it when you need to search genes by symbol/ID and retrieve annotations (RefSeq, GO, location, phenotype) for single or batch gene lists.

Search for gene expression DataSets and Profiles in the NCBI GEO database. Use this skill when the user wants to find microarray, RNA-seq, or other genomic data by keywords, organism, author, or specific fields.

Unified CLI/Python interface for querying genomic, proteomic, structure, and expression data across 20+ bioinformatics databases; use when you need fast, scriptable retrieval by gene/protein IDs or keywords.

Query the NHGRI-EBI GWAS Catalog to retrieve SNP–trait associations, study metadata, and (when available) summary statistics when you need evidence for a variant, trait/disease, gene, or genomic region.

Access JASPAR database for transcription factor binding profiles (matrices), collections, and species via REST API. Use when user wants to search for transcription factors, retrieve matrix details (PFM/PWM), infer profiles from protein sequences, or explore JASPAR collections.

Generates a weekly academic literature report based on keywords using PubMed. Use when the user wants to track recent research progress on a specific topic, automatically retrieving, classifying, and summarizing relevant papers from the last 7 days.

Analyzes research hotspots and recommends literature based on a disease or topic. Use when the user wants to identify current research trends, hot topics, or get literature recommendations for a specific medical field or disease.

Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.

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.

Evidence-Based Medicine diagnostic test calculator. Computes sensitivity, specificity, PPV, NPV, likelihood ratios, NNT, and pre/post-test probability from 2x2 contingency table inputs.

Generate renderable, scientific-style SVG graphics directly from natural-language requirements (no image models). Use when users ask for an image/picture/scientific diagram/visualization poster or explicitly request SVG output for web-embeddable vector graphics.

Recommend academic journals based on manuscript topic, abstract, and impact factor expectations. Use when the user wants to find suitable journals for their research manuscript, especially when they provide a topic, abstract, and target Impact Factor.

Search and locate relevant content within a local knowledge base (files, indices, or PageIndex). Use when you need verifiable citations (file + page/paragraph) to support answers from local sources.

A medical assistant tool that transforms complex biochemical laboratory test results into clear, patient-friendly explanations with safety disclaimers and severity flags.

Integrates multiple news sources into a single, cohesive press release using an inverted pyramid structure and AP style. Use when you have raw news content and a topic, and need a professional press release.

Generates a structured reading tweet from an academic paper (PDF, Word, or Text), highlighting specific product advantages. Use when the user wants to turn a document into a social media post or reading summary.