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bids
【数据与研究】Organizes, queries, validates, and converts Brain Imaging Data Structure (BIDS) datasets. Supports organizing neuroscience and biomedical data (MRI, EEG, MEG, iEEG, PET, microscopy, NIRS, motion capture, EMG, MR spectroscopy, behavioral), querying BIDS layouts, validating compliance, converting DICOM to BIDS, writing metadata sidecars, or creating BI…
ncats-arax
【效率与协作】Queries the NCATS Translator ARAX production API for bounded, typed, provenance-rich one-hop and endpoint-pinned two-hop biomedical knowledge-graph relationships. Use for Biolink-constrained RTX-KG2 lookup, explicit selected-provider ARAX federation, separate entity normalization, qualifier-aware graph traversal, and inspection of TRAPI edge bindings…
paperclip
【文档与办公】Searches and reads biomedical papers, FDA/PMDA/EMA documents, clinical trials, and protein records with the GXL Paperclip CLI and Python SDK. Supports source-scoped search, full-text grep, metadata SQL, map/reduce extraction, figure analysis, optional repositories and claim verification, and line-pinned citations. Use when a task names GXL paperclip,…
benchmarking-clinical-ner
【数据与研究】Score an OpenMed clinical or biomedical NER model against a user-supplied gold corpus with entity-level precision, recall, and F1, then break errors down per label. Use when the user wants a seqeval-style scorecard, strict vs partial (relaxed) span matching, a per-label confusion matrix, false-negative / false-positive examples, or to debug why a mod…
building-with-openmed
【效率与协作】Orient and bootstrap any project that uses OpenMed, the on-device clinical and biomedical NLP library, for named-entity recognition, PHI de-identification, FHIR export, and evaluation. Use when the user mentions OpenMed, wants to install it, asks which OpenMed capability or model fits a task, or is starting to build a clinical/medical text pipeline a…
choosing-openmed-models
【数据与研究】Discover and pick the right OpenMed model for a clinical or biomedical task, domain, or language. Use when the user asks which OpenMed model to use, wants to list model categories, find a Disease vs Oncology vs Privacy/PII model, get a PII model for a specific language, search models by size or task, or inspect a model's labels and metadata before lo…
extracting-clinical-entities
【效率与协作】Run clinical and biomedical named-entity recognition on medical text with OpenMed's analyze_text. Use when the user wants to extract diseases, drugs, anatomy, genes, or other biomedical entities from notes; needs NER output as dict/json/html/csv; wants to filter by confidence, group entities, toggle sentence detection, or save spans to JSONL; or want…
loading-openmed-models
【效率与协作】Load OpenMed clinical/biomedical NER models from the Hugging Face Hub or a local path and reuse them efficiently across calls. Use when the user wants to load an OpenMed model, control the model cache, run fully offline after a one-time download, reuse a ModelLoader to avoid reloading, set a cache_dir or device, or pick between a registry key, a full…
mining-pubmed-literature
【效率与协作】Searches and fetches PubMed and PMC via NCBI E-utilities (ESearch then EFetch/ESummary) to gather biomedical evidence and build text corpora. Use when the user wants citations for a condition or drug, abstracts to summarize, MeSH-based searches, or a corpus of literature to run NER over. Trigger keywords: PubMed, PMC, NCBI, E-utilities, ESearch, EFet…
running-zeroshot-ner
【数据与研究】Extract arbitrary, custom entity types from clinical or biomedical text with no fine-tuning using OpenMed's GLiNER / GLiNER2 zero-shot support. Use when the user wants to define their own labels on the fly (e.g. Drug, Symptom, Device, Procedure), has no labelled data or a label set not covered by a fine-tuned model, or asks about openmed zero deps/in…
literature-review
【文档与办公】Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professi…
fea-mesh-generator
【开发与工程】Finite element mesh generation skill optimized for biomedical geometries including implants, anatomical structures, and tissue models
pubmed-literature-miner
【开发与工程】Biomedical literature mining using PubMed/MEDLINE for systematic review support
tooluniverse-biomedical-fact-lookup
【数据与研究】Answer biomedical FACTUAL / recall / multiple-choice questions by querying ToolUniverse database tools instead of answering from memory. Triggers on any 'which gene/drug/variant/disease/pathway/miRNA/TF...' lookup, any question phrased 'according to <database>' (DisGeNet, OMIM, MSigDB, miRDB, GTRD, MGI, Ensembl, ClinVar, ChEMBL, OpenTargets, Reactome…
tooluniverse-bioinformatics-resource-discovery
【数据与研究】Discover which bioinformatics software tool, biomedical REST API, R/Bioconductor package, CRAN package, or training material exists for a task, before writing analysis code or building a pipeline. Covers ELIXIR bio.tools (30,000+ software tools/databases by keyword, EDAM topic, or EDAM operation), SmartAPI (biomedical API registry, incl. NCATS Transl…
tooluniverse-biomedical-fact-lookup
【数据与研究】Answer biomedical FACTUAL / recall / multiple-choice questions by querying ToolUniverse database tools instead of answering from memory. Triggers on any 'which gene/drug/variant/disease/pathway/miRNA/TF...' lookup, any question phrased 'according to <database>' (DisGeNet, OMIM, MSigDB, miRDB, GTRD, MGI, Ensembl, ClinVar, ChEMBL, OpenTargets, Reactome…
tooluniverse-bioinformatics-resource-discovery
【数据与研究】Discover which bioinformatics software tool, biomedical REST API, R/Bioconductor package, CRAN package, or training material exists for a task, before writing analysis code or building a pipeline. Covers ELIXIR bio.tools (30,000+ software tools/databases by keyword, EDAM topic, or EDAM operation), SmartAPI (biomedical API registry, incl. NCATS Transl…
tooluniverse-biomedical-fact-lookup
【数据与研究】Answer biomedical FACTUAL / recall / multiple-choice questions by querying ToolUniverse database tools instead of answering from memory. Triggers on any 'which gene/drug/variant/disease/pathway/miRNA/TF...' lookup, any question phrased 'according to <database>' (DisGeNet, OMIM, MSigDB, miRDB, GTRD, MGI, Ensembl, ClinVar, ChEMBL, OpenTargets, Reactome…