For data

Compare two datasets to find differences, added/removed rows, changed values. Use for data validation, ETL verification, or tracking changes.

Merge pandas DataFrames from multiple construction sources. Handle different schemas, keys, and data quality issues.

Differential binding analysis using DiffBind. Compare ChIP-seq peaks between conditions with statistical rigor. Requires replicate samples. Outputs differentially bound regions with fold changes and p-values. Use when comparing ChIP-seq binding between conditions.

Coordinate distributed processing with parallel execution, forked skills, and isolated work units. Use when you need distributed processing or isolated work units. Not for sequential tasks or single-threaded workflows.

**Why?** Manually downloading transcripts one-by-one is tedious and error-prone. This skill automates bulk transcript downloads with rate limiting, progress tracking, and resume capability.

Set up earnings tasks for a ticker with CSV persistence and Claude task tracking

评价 Skill 执行结果的 Skill。当需要评价产出质量、判断是否需要迭代时触发。触发词：评价、evaluate、打分、怎么样、效果如何。

Use for creating websets, running searches, importing CSV data, managing items, and adding enrichments to extract structured data.

Gera arquivos Excel, CSV ou JSON para download pelo usuario. Use quando o usuario pedir para exportar dados, criar planilha, gerar relatorio ou baixar informacoes. SEMPRE use esta skill em vez de Write para criar arquivos que o usuario precisa baixar.

**Why?** Manually tracking YouTube videos is tedious and error-prone. This skill automates extracting video metadata (titles, durations, URLs) into a CSV for systematic transcript downloading and anal

Expert guidance for Microsoft Fabric Real-Time Intelligence (RTI) using the Fabric RTI MCP Server. Execute KQL queries on Eventhouse, manage Eventstreams for real-time data processing, create Activator triggers for alerting, and manage Map items. Use when working with Fabric RTI, KQL, real-time analytics, streaming data, or event-driven applications.

获取中国A股和ETF市场数据。使用场景：(1) 查询股票历史数据，(2) 获取ETF净值走势，(3) 指定时间范围的数据提取。支持通过股票代码和天数参数获取OHLCV（开盘价、最高价、最低价、收盘价、成交量）数据。

Create and manage data pipelines using the FlowerPower framework with Hamilton DAGs and uv. Use when users request creating flowerpower projects, pipelines, Hamilton dataflows, or ask about flowerpower configuration, execution, or CLI commands.

Fill PDF forms programmatically with data from JSON, CSV, or dictionaries. Support for text fields, checkboxes, and dropdowns. Batch filling available.

Running batch inference on Google Cloud (also known as Vertex AI)

Gemma PQN Data Processor

Convert addresses to coordinates (geocoding) and coordinates to addresses (reverse geocoding). Use for location data enrichment or address validation.

Automate George online banking (Erste Bank / Sparkasse Austria) using Playwright: login/session (phone approval), list accounts + balances, and download statements/exports/transactions (CAMT53, MT940, CSV/JSON/OFX/XLSX). Use when the user mentions George, Erste/Sparkasse, account statements, CAMT53/MT940, or transaction exports.

Master geographic and mapping visualizations with GeoViews. Use this skill when creating interactive maps, visualizing point/polygon/line geographic data, building choropleth maps, performing spatial analysis (joins, buffers, proximity), working with coordinate reference systems, or integrating tile providers and basemaps.

Workflow and ready-to-import helpers for connecting to Google Drive with a service account, listing folders, and routing files based on MIME type. Use this skill whenever you need to download/export Docs, Sheets, Slides, Forms, or arbitrary binaries and surface their contents as pandas tables or local artifacts.

Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases. Use when importing CSV/JSON/Parquet files, pulling from S3/GCS buckets, consuming API feeds, or building ETL pipelines.

Create interactive HTML plots with plotly and bokeh for exploratory data analysis and web-based sharing of omics visualizations. Use when building zoomable, hoverable plots for data exploration or web dashboards.

Analyzes iron condor credit spreads with OTM put and call spreads for range-bound trading. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting sideways price action, want to collect premium in high IV, analyzing range-bound opportunities, or implementing neutral income strategies on stocks with defined trading ranges.

Use when Java Streams API for functional-style data processing. Use when processing collections with streams.

Complete guide for Apache Kafka stream processing including producers, consumers, Kafka Streams, connectors, schema registry, and production deployment

车险KPI计算专家。基于每周六截止的年度累计CSV数据，精确计算16个核心KPI指标，严格遵循既定公式。

Calculate construction labor rates with overhead, benefits, and productivity factors. Regional rate databases and crew composition.

Detect language of text with confidence scores, support for 50+ languages, and batch text classification.

Le arquivos Excel (.xlsx, .xls) e CSV enviados pelo usuario. Use quando o usuario anexar um arquivo e pedir para analisar, importar ou processar os dados. Retorna o conteudo como JSON para analise.

CRISPR library design for genetic screens. Covers sgRNA selection, library composition, control design, and oligo ordering. Use when designing custom sgRNA libraries for knockout, activation, or interference screens.

Write titles that describe the problem or outcome:

加载并预处理保险保单周度数据，支持智能周期检测、多周数据加载、数据验证和清洗。在开始任何保险数据分析任务时使用。

Look up the time zone of a given city and return the local time.

This skill provides guidance for analyzing log files across date ranges and producing summary statistics. Use when tasks involve parsing log files, counting log entries by severity (ERROR, WARNING, INFO), aggregating by date ranges (today, last N days, month-to-date), or producing CSV reports from log data.

Analyzes long call butterfly spreads with 3 strikes and 4 legs for neutral outlook. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting minimal price movement, want low-cost defined-risk strategy, analyzing pinning opportunities, or evaluating tight-range neutral positions on stocks near technical levels.

Analyzes long straddle volatility plays with ATM call and put at same strike. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting large price movement in either direction, analyzing earnings plays, evaluating volatility opportunities, or assessing binary event outcomes on high IV stocks.

Analyzes long strangle volatility plays with OTM call and put at different strikes. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting very large price movement, want lower-cost alternative to straddle, analyzing high-volatility events, or evaluating wide-range breakout opportunities on stocks with elevated IV.

Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

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Filter and screen stocks by financial metrics like P/E ratio, market cap, dividend yield, and growth rates. Analyze and compare stocks from CSV data.

Python data processing pipelines with modular architecture. Use when building content processing workflows, implementing dispatcher patterns, integrating Google Sheets/Drive APIs, or creating batch processing systems. Covers patterns from rosen-scraper, image-analyzer, and social-scraper projects.

Parse and create FCS (Flow Cytometry Standard) files v2.0-3.1. Read event data as NumPy arrays, extract channel metadata, handle multi-dataset files, export to CSV/FCS. For advanced gating and compensation use FlowKit.

Interactive visualization with Plotly. 40+ chart types (scatter, line, bar, heatmap, 3D, statistical, geographic) with hover, zoom, and pan. Use for exploratory analysis, dashboards, and presentations. Two APIs: Plotly Express (quick, DataFrame-oriented) and Graph Objects (fine-grained control). For static publication figures use matplotlib; for statistical grammar use seaborn.

Statistical visualization library built on matplotlib with native pandas DataFrame support. Automatic aggregation, confidence intervals, and grouping for distribution plots (histplot, kdeplot), categorical comparisons (boxplot, violinplot, stripplot), relational plots (scatterplot, lineplot), regression plots (regplot, lmplot), matrix plots (heatmap, clustermap), and multi-variable grids (pairplot, jointplot, FacetGrid). Use seaborn for statistical summaries with minimal code; use matplotlib for fine-grained figure control; use plotly for interactive HTML output.

Statistical visualization built on matplotlib with pandas integration. Distribution plots (histplot, kdeplot, violinplot, boxplot), relational plots (scatterplot, lineplot), categorical comparisons, regression, correlation heatmaps. Automatic aggregation and CI. For interactive plots use plotly; for low-level control use matplotlib.

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Pipeline for analyzing Neuropixels extracellular electrophysiology recordings. Covers probe geometry loading (ProbeInterface), spike sorting with Kilosort via SpikeInterface, quality metrics computation, unit curation (ISI violations, firing rate, signal-to-noise), and post-sort analysis (PSTH, tuning curves, population decoding) using pandas and matplotlib. Designed for acute and chronic Neuropixels 1.0/2.0/Ultra recordings from rodent and primate experiments.

File-upload bridge for Claude Code on the Web. CCotw has no native file mount; this skill creates a throwaway GitHub branch the user can drop files onto via the github.com web UI, then fetches them locally on the next turn. Use when the user wants to upload, share, or send files into the session, or when a task clearly needs files the user has on disk that aren't in the repo.

Compute technical indicators like RSI, MACD, Bollinger Bands, SMA, EMA for a stock. Use when user asks about technical analysis, indicators, RSI, MACD, moving averages, overbought/oversold, or chart analysis.