Total 30,832 skills, Data Processing has 1471 skills
Showing 12 of 1471 skills
Generate publication-ready scientific figures in Python/matplotlib with a consistent figures4papers house style. Use when creating or refining academic bar/trend/heatmap/scatter/multi-panel figures, enforcing visual consistency, or exporting paper-ready PNG/PDF/SVG outputs.
Locate and adapt real plotting examples from the figures4papers repository. Use when users ask for a figure in the style of specific papers/projects, want the closest existing script template, or need fast script selection by chart type/domain before customization.
Fetch analytics from Umami. Use when the user asks about umami, analytics, website traffic, daily stats, pageviews, visitors, how is my site doing, traffic report, site performance, bounce rate, visitor count, active users, who is on my site, or website statistics.
Remove backgrounds from images using segmentation. Support for color-based, edge detection, and AI-assisted removal methods. Batch processing available.
Production-ready single-cell and expression matrix analysis using scanpy, anndata, and scipy. Performs scRNA-seq QC, normalization, PCA, UMAP, Leiden/Louvain clustering, differential expression (Wilcoxon, t-test, DESeq2), cell type annotation, per-cell-type statistical analysis, gene-expression correlation, batch correction (Harmony), trajectory inference, and cell-cell communication analysis. NEW: Analyzes ligand-receptor interactions between cell types using OmniPath (CellPhoneDB, CellChatDB), scores communication strength, identifies signaling cascades, and handles multi-subunit receptor complexes. Integrates with ToolUniverse gene annotation tools (HPA, Ensembl, MyGene, UniProt) and enrichment tools (gseapy, PANTHER, STRING). Supports h5ad, 10X, CSV/TSV count matrices, and pre-annotated datasets. Use when analyzing single-cell RNA-seq data, studying cell-cell interactions, performing cell type differential expression, computing gene-expression correlations by cell type, analyzing tumor-immune communication, or answering questions about scRNA-seq datasets.
Web scraping inteligente multi-estrategia. Extrai dados estruturados de paginas web (tabelas, listas, precos). Paginacao, monitoramento e export CSV/JSON.
Analyze commodity markets including futures curve dynamics, roll yield, and supply/demand fundamentals. Use when the user asks about commodity investing, commodity ETFs, contango, backwardation, roll yield, commodity indices (GSCI, BCOM), or commodities as an inflation hedge. Also trigger when users mention 'oil prices', 'gold as a safe haven', 'agricultural futures', 'convenience yield', 'storage costs', 'natural gas', 'copper demand', or ask why commodity ETF returns differ from spot price changes.
Plotly Chart Generator - Auto-activating skill for Visual Content. Triggers on: plotly chart generator, plotly chart generator Part of the Visual Content skill category.
Regular expression expert for crafting, debugging, and explaining patterns
Query the ExoPriors Scry API -- SQL-over-HTTPS search across 229M+ entities spanning forums, papers, social media, government records, and prediction markets. Includes cross-platform author identity resolution (actors, people, aliases), OpenAlex academic graph navigation (authors, citations, institutions, concepts), shareable artifacts, and structured agent judgements. Use when the task involves: Scry API, ExoPriors, /v1/scry/query, scry.search, scry.entities, materialized views, corpus search, epistemic infrastructure, 229M entities, lexical search, BM25, structured agent judgements, scry shares, cross-corpus analysis, who is this person, cross-platform identity, OpenAlex, citation graph, coauthor graph, academic papers, author lookup. NOT for: semantic/vector search composition or embedding algebra (use scry-vectors), LLM-based reranking (use scry-rerank), or the user's own local Postgres / non-ExoPriors data sources.
Crypto 单因子量化研究服务 Skill。当用户说"写一个因子"、"研究因子"、"量化打工"、 "提交因子"、"因子回测"时加载此 Skill。 Agent 负责编写因子插件代码并通过 HTTP 接口与服务器交互， 服务器负责所有数据处理和计算，Agent 本地无需任何市场数据。
Use when working with R ggplot2 package, especially ggplot2 4.0+ features. Covers S7 migration (@ property access), theme defaults with ink/paper/accent, element_geom(), from_theme(), theme shortcuts (theme_sub_*), palette themes, labels with dictionary/attributes, discrete scale improvements (palette, continuous.limits, minor_breaks, sec.axis), position aesthetics (nudge_x/nudge_y, order), facet_wrap dir/space/layout, boxplot/violin/label styling, stat_manual(), stat_connect(), coord reversal.