datacommons-client
Work with Data Commons, a platform providing programmatic access to public statistical data from global sources. Use this skill when working with demographic…
Skills
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Updated 10-26 00:15
Data & analytics
16,951 results
datamol
Pythonic wrapper around RDKit with simplified interface and sensible defaults. Preferred for standard drug discovery: SMILES parsing, standardization,…
ena-database
Access European Nucleotide Archive via API/FTP. Retrieve DNA/RNA sequences, raw reads (FASTQ), genome assemblies by accession, for genomics and bioinformatics…
ensembl-database
Query Ensembl genome database REST API for 250+ species. Gene lookups, sequence retrieval, variant analysis, comparative genomics, orthologs, VEP predictions,…
flowio
Parse FCS (Flow Cytometry Standard) files v2.0-3.1. Extract events as NumPy arrays, read metadata/channels, convert to CSV/DataFrame, for flow cytometry data…
labarchive-integration
Electronic lab notebook API integration. Access notebooks, manage entries/attachments, backup notebooks, integrate with Protocols.io/Jupyter/REDCap, for…
nemo-curator
GPU-accelerated data curation for LLM training. Supports text/image/video/audio. Features fuzzy deduplication (16× faster), quality filtering (30+ heuristics),…
neurokit2
Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when…
pydicom
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical…
pytdc
Therapeutics Data Commons. AI-ready drug discovery datasets (ADME, toxicity, DTI), benchmarks, scaffold splits, molecular oracles, for therapeutic ML and…
scikit-survival
Comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival. Use this skill when working with censored survival…
scvi-tools
This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial…
tensorboard
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML…
umap-learn
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for…
building-with-sqlalchemy-orm
Build production database layers with SQLAlchemy ORM and PostgreSQL. This skill should be used when teaching students to define data models, manage sessions,…
bi-fundamentals
BI fundamentals with metric definition, KPI calculation, dimensional modeling, dashboard optimization, and data storytelling. 40+ metric examples and…
review-plugin-submission
Audit a Cursor plugin for marketplace readiness. Use when validating manifests, component metadata, discovery paths, and submission quality before publishing.
story-long-scan
Long-form web novel ranking scan. Analyze ranking data from platforms such as Qidian, Fanqie, and Jinjiang, and distill market trends and popular genres. Trigger methods: /story-long-scan, /long-form scan, "what's hot in long-form", "Qidian rankings".
qonto-vat-return
French VAT return (CA3, form 3310-CA3) preparer for Qonto accounts. Builds the declaration box by box from real account data — collected VAT per rate…
how-to-store-sqlite-as-nosql-store
Discover how to leverage SQLite's JSON support to build a NoSQL-like document store, complete with TTL-based expiration, within this powerful embedded database.
azure-data-tables-py
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
azure-storage-blob-py
Azure Blob Storage SDK for Python. Use for uploading, downloading, listing blobs, managing containers, and blob lifecycle.
matplotlib
Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots.
scikit-learn
Machine learning in Python with scikit-learn. Use for classification, regression, clustering, model evaluation, and ML pipelines.