Agent Skills Hub

literature-review

Conduct systematic literature reviews across PubMed, arXiv, and Semantic Scholar with AI-driven synthesis, verified citations, and mandatory schematic visualization.

scientific-visualization

Meta-skill for generating publication-ready scientific figures, multi-panel layouts, and journal-compliant visualizations using Python's matplotlib, seaborn, and plotly libraries.

xhs-viral-post

AI-powered generator for viral XiaoHongShu posts, including titles, captions, hashtags, cover image prompts, and posting strategies.

data-quality-frameworks

Implement production-grade data quality validation using Great Expectations, dbt tests, and data contracts to ensure reliable pipelines.

competitor-analysis

Conduct strategic competitive analysis to map market landscapes, identify direct competitors, synthesize strengths and weaknesses, and uncover differentiation opportunities.

paper-reproduce

Systematic methodology for reproducing published academic papers using provided data, including sample selection, statistical verification, and automated reporting.

massive-context-mcp

Process massive files and large codebases (10M+ tokens) by recursively chunking, sub-querying, and aggregating results to overcome LLM context limits.

light-curve-preprocessing

Preprocessing and cleaning astronomical light curves using Lightkurve. Tools for outlier removal, flattening, trend detrending, and quality flag handling for time-series analysis.

excel-report-generator

Automate Excel report generation from CSVs, databases, or data structures using pandas and openpyxl. Supports chart creation, custom styling, template-based workflows, and data analysis.

tavily-web

Advanced web search, content extraction, and site crawling capabilities using the Tavily API, optimized for AI agent research and data gathering.

single-cell-rna-qc

Automated single-cell RNA-seq quality control pipeline following scverse best practices. Performs MAD-based outlier detection, cell filtering, and diagnostic visualization for .h5ad and .h5 datasets.

polars

High-performance in-memory DataFrame library for Python and Rust. Features lazy evaluation, parallel execution, and an Apache Arrow backend for efficient ETL, data processing, and faster pandas alternatives.