Total 50,396 skills, Data Processing has 2557 skills
Showing 12 of 2557 skills
Combines and synthesizes outputs from parallel DAG branches. Handles merge strategies, conflict resolution, and result formatting. Activate on 'aggregate results', 'combine outputs', 'merge branches', 'synthesize results', 'fan-in'. NOT for execution (use dag-parallel-executor) or scheduling (use dag-task-scheduler).
Run forensic ratio and trend checks from SEC filing data to validate or challenge Shenanigans hypotheses. Use when users ask for quantitative red-flag checks, earnings quality diagnostics, or quarter-over-quarter anomaly detection.
Use when creating infographics, data visualizations, process diagrams, timelines, or comparisons - generates branded infographics using @antv/infographic with 114 templates across 7 categories. Triggers on "create infographic", "make infographic", "visualize data", "timeline", "process diagram".
Create publication-quality matplotlib/seaborn charts with readable axes, tight layout, and curated palettes.
Detect, classify, and QC viral contigs.
Market data management: real-time vs delayed feeds, Level 1/2/3 data, data vendors, consolidated tape, market data licensing, distribution, and infrastructure.
Position sizing: Kelly criterion, fractional Kelly, risk budgeting, maximum position sizes, conviction weighting.
Data Catalog Updater - Auto-activating skill for Data Pipelines. Triggers on: data catalog updater, data catalog updater Part of the Data Pipelines skill category.
Comprehensive systems biology and pathway analysis using multiple pathway databases (Reactome, KEGG, WikiPathways, Pathway Commons, BioModels). Performs pathway enrichment, protein-pathway mapping, keyword searches, and systems-level analysis. Use when analyzing gene sets, exploring biological pathways, or investigating systems-level biology.
Execute read-only SQL queries against multiple Microsoft SQL Server databases. Use when: (1) querying MSSQL/SQL Server databases, (2) exploring database schemas/tables, (3) running SELECT queries for data analysis, (4) checking database contents. Supports multiple database connections with descriptions for intelligent auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.
Computational analysis framework for spatial multi-omics data integration. Given spatially variable genes (SVGs), spatial domain annotations, tissue type, and disease context from spatial transcriptomics/proteomics experiments (10x Visium, MERFISH, DBiTplus, SLIDE-seq, etc.), performs comprehensive biological interpretation including pathway enrichment, cell-cell interaction inference, druggable target identification, immune microenvironment characterization, and multi-modal integration. Produces a detailed markdown report with Spatial Omics Integration Score (0-100), domain-by-domain characterization, and validation recommendations. Uses 70+ ToolUniverse tools across 9 analysis phases. Use when users ask about spatial transcriptomics analysis, spatial omics interpretation, tissue heterogeneity, spatial gene expression patterns, tumor microenvironment mapping, tissue zonation, or cell-cell communication from spatial data.
Ingest, QC, and map reads with reproducible outputs. Use for raw read processing and coverage stats.