Total 50,474 skills, Data Processing has 2559 skills
Showing 12 of 2559 skills
Query the BCRA (Banco Central de la República Argentina) Central de Deudores API to check the credit status of individuals or companies in Argentina's financial system. Use when the user asks to check someone's debt situation, credit report, financial standing, rejected checks, or credit history using a CUIT/CUIL/CDI number. Also use when the user mentions "central de deudores", "situación crediticia", "deudas BCRA", "cheques rechazados", "historial crediticio", "informe crediticio", or wants to know if a person or company has debts reported in Argentina's financial system.
Configure data accelerators for local materialization and caching in Spice (Arrow, DuckDB, SQLite, Cayenne, PostgreSQL, Turso). Use when asked to "accelerate data", "enable caching", "materialize dataset", "configure refresh", "set up local storage", "improve query performance", "choose an accelerator", or "configure snapshots".
Extract structured forensic evidence from SEC filings (10-K, 10-Q, 8-K, S-1 proxy appendices) for accounting-quality analysis. Use when a user asks to review filings, gather red flags, or prepare inputs for Shenanigans classification.
Create reports in Frappe including Report Builder, Query Reports (SQL), and Script Reports (Python + JS). Use when building data analysis views, dashboards, or custom reporting features.
Neo4j Cypher Shell skill. Connect to instances, run Cypher queries, and retrieve full graph schemas via cypher-shell CLI.
Expert data engineer for ETL/ELT pipelines, streaming, data warehousing. Activate on: data pipeline, ETL, ELT, data warehouse, Spark, Kafka, Airflow, dbt, data modeling, star schema, streaming data, batch processing, data quality. NOT for: API design (use api-architect), ML training (use ML skills), dashboards (use design skills).
Map scRNA-seq atlases onto spatial transcriptomics slides using omicverse's Single2Spatial workflow for deep-forest training, spot-level assessment, and marker visualisation.
CLI tool for web scraping - extract data from websites via terminal without programming. Powerful extract commands for HTTP requests and browser automation.
Interpret genetic variants (SNPs) from GWAS studies by aggregating evidence from multiple databases (GWAS Catalog, Open Targets Genetics, ClinVar). Retrieves variant annotations, GWAS trait associations, fine-mapping evidence, locus-to-gene predictions, and clinical significance. Use when asked to interpret a SNP by rsID, find disease associations for a variant, assess clinical significance, or answer questions like "What diseases is rs429358 associated with?" or "Interpret rs7903146".
Integrate and analyze multiple omics datasets (transcriptomics, proteomics, epigenomics, genomics, metabolomics) for systems biology and precision medicine. Performs cross-omics correlation, multi-omics clustering (MOFA+, NMF), pathway-level integration, and sample matching. Coordinates ToolUniverse skills for expression data (RNA-seq), epigenomics (methylation, ChIP-seq), variants (SNVs, CNVs), protein interactions, and pathway enrichment. Use when analyzing multi-omics datasets, performing integrative analysis, discovering multi-omics biomarkers, studying disease mechanisms across molecular layers, or conducting systems biology research that requires coordinated analysis of transcriptome, genome, epigenome, proteome, and metabolome data.
Production-ready RNA-seq differential expression analysis using PyDESeq2. Performs DESeq2 normalization, dispersion estimation, Wald testing, LFC shrinkage, and result filtering. Handles multi-factor designs, multiple contrasts, batch effects, and integrates with gene enrichment (gseapy) and ToolUniverse annotation tools (UniProt, Ensembl, OpenTargets). Supports CSV/TSV/H5AD input formats and any organism. Use when analyzing RNA-seq count matrices, identifying DEGs, performing differential expression with statistical rigor, or answering questions about gene expression changes.
Analyze mass spectrometry proteomics data including protein quantification, differential expression, post-translational modifications (PTMs), and protein-protein interactions. Processes MaxQuant, Spectronaut, DIA-NN, and other MS platform outputs. Performs normalization, statistical analysis, pathway enrichment, and integration with transcriptomics. Use when analyzing proteomics data, comparing protein abundance between conditions, identifying PTM changes, studying protein complexes, integrating protein and RNA data, discovering protein biomarkers, or conducting quantitative proteomics experiments.