Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production pipelines.

Deep learning for single-cell analysis using scvi-tools and scverse ecosystem. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping, (7) RNA velocity with veloVI, or (8) QC analysis of single-cell RNA-seq data. Triggers include scVI, scANVI, totalVI, QC, quality control, batch correction, integration, multi-modal.

A conversational framework for systematic scientific problem selection, project ideation, troubleshooting, and strategic decision making.

Monitor competitor product pages and alert when prices change.

Answer data questions -- from quick lookups to full analyses

Create publication-quality visualizations with Python

Profile and explore a dataset to understand its shape, quality, and patterns

QA an analysis before sharing -- methodology, accuracy, and bias checks

Write optimized SQL for your dialect with best practices

Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.

Query decomposition and multi-source search orchestration. Breaks natural language questions into targeted searches per source, translates queries into source-specific syntax, ranks results by relevance, and handles ambiguity and fallback strategies.

Manages connected MCP sources for enterprise search. Detects available sources and handles source priority ordering.

Generate SOX sample selections, testing workpapers, and control assessments

Convert incidents into structured GitHub issues.

Categorize messages and propose replies and next steps.

Legacy fallback for high-level campaign PM structure. Prefer launch-strategy for launch execution and canonical Core 9 skills for channel work. Use this template when a generic campaign framework is explicitly needed.