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Found 65 Skills
Vendor-neutral skill to analyze onboarding funnel dropoff and propose prioritized interventions.
Visualize your highlights and their connections in an interactive 2D graph
High-performance data analysis using Polars - load, transform, aggregate, visualize and export tabular data. Use for CSV/JSON/Parquet processing, statistical analysis, time series, and creating charts.
Financial time series analysis method toolkit. Covers stocks / commodity futures / cryptocurrencies / ETFs / foreign exchange / indices, full process from data acquisition to high-level analysis. Built-in 70+ analysis methods, covering 8 major method domains: time series testing, predictive modeling, cross-asset relationships, volatility risk, portfolio optimization, state recognition, commodity-specific analysis and network analysis. Tushare MCP tool (A shares/Hong Kong stocks/US stocks/futures/funds/macro) is preferred for data acquisition, and yfinance scripts are used to supplement assets not covered by tushare such as commodity futures (CL=F) and crypto (BTC-USD).
Aylien News API integration. Manage data, records, and automate workflows. Use when the user wants to interact with Aylien News API data.
Find substitute materials using CWICR data. Identify equivalent alternatives based on function, cost, and availability.
Vendor-neutral skill to score customer churn risk from account signals and produce prioritized retention actions.
Inject knowledge into JSON data context.
Detect anomalies in data using statistical and ML methods. Z-score, IQR, Isolation Forest, and time-series anomalies.
Perform technical analysis on stock K-line data, calculate indicators such as MA/MACD/RSI, and judge trends and trading signals. Trigger scenarios: (1) "Analyze the technical aspects of Moutai" (2) "Check if this stock is buyable" (3) "Technical analysis 600519" (4) Used when needing to judge stock trends and trading points. Need to use data-collect to obtain data first
DuckDB SQL reference for MotherDuck. Use when you need exact DuckDB syntax, function behavior, supported MotherDuck SQL features, or to resolve whether PostgreSQL-oriented SQL will fail on MotherDuck.
万行以上 Excel 数据集的高性能分析引擎。提供 openpyxl read_only 流式读取(iter_rows 支持 10 万行以上)、Parquet 转换加速、内存优化、分块处理和大文件写入模式。**遇到以下任一情况就主动使用本 skill**:①数据行数 ≥ 10k(由 sn-da-excel-workflow 的行数评估步骤触发);②用户出现触发词:大文件 / 大数据量 / 性能优化 / 内存不足 / OOM / 百万行 / 十万行 / 流式读取 / Parquet / 分块处理 / large file / big data / streaming read / chunked processing;③直接使用 pd.read_excel() 导致超时或内存溢出;④用户明确要求对大规模数据集进行高性能处理。仅不用于:小于 10k 行的常规 Excel 分析(使用 sn-da-excel-workflow 即可)。