>

Help recreate Our World in Data (OWID) charts (line, bar, bubble) as faithfully as possible in this repo’s Jupyter notebooks, using pandas + Matplotlib (and Plotly when requested), with correct data,

Telegram DM sending from CSV, rate limiting, idempotency

Read, write, append, and list local files in the session's working directory. Use when you need to persist output to disk, read input files, or manipulate file system safely. Supports text files, JSON, CSV, Markdown.

在新数据集接入前检查字段、单位、缺失率、异常值与可用性。；use for data, dataset, audit workflows；do not use for 伪造统计结果, 替代正式数据治理平台.

分析退货原因并区分产品问题、预期错配、物流问题和描述问题。；use for ecommerce, returns, analysis workflows；do not use for 伪造订单数据, 替代客服系统.

Double-entry, full-cycle accounting suite built for AI agents. Converts bank CSVs, OFX, and QBO files into balanced, auditable books — balance sheet, income statement, general ledger, trial balance. All data stays in a single local SQLite file.

>

Upload any data file (CSV, Excel, JSON, SQL export) and get a complete analysis report with insights, anomalies, and actionable recommendations — no code required.

3-in-1 China 12306 query — tickets, route stops, transfer plans. Zero login. Filter 高铁/动车/火车 by type, time, duration. Pure Python, text/json/csv output. 火车票/余票/经停站/中转换乘.

Analyze bank transactions, categorize spending, track monthly budgets, detect overspending and anomalies. Outputs interactive HTML report.

Financial analysis and research workflows for market research, equity research, comparable companies, precedent transactions, and DCF valuation. Use when asked to build or critique DCF models, comps/precedents tables, competitor or strategy analysis, market sizing, or to deliver analyst-ready outputs in Excel, PowerPoint, or Markdown from CSV/Excel/SQL/API/web data.

Data processing pipelines for OpenClaw. Deploy skills from the Expanso marketplace to transform, analyze, and process data locally.

与 Quicker 自动化工具集成，读取、搜索和执行 Quicker 动作列表。支持 CSV 和数据库双数据源，智能匹配用户需求并调用本地 QuickerStarter 执行。

>

Read analysis results. Use when user asks about maximum stress, extracting displacements, reaction forces, or exporting results. Post-processes ODB files.

When the user needs to set up multiple academic courses in a learning management system (Canvas/LMS) from structured data sources. This skill automates the entire workflow extracting course schedules from emails/attachments, matching instructors from CSV files, creating courses, enrolling teachers, publishing announcements with class details, uploading syllabi, enabling resource sharing for instructors teaching multiple courses, and publishing all courses. Triggers include course schedule setup, Canvas/LMS administration, academic term preparation, instructor assignment, syllabus distribution, and multi-course management.

Complete guide for Apache Spark data processing including RDDs, DataFrames, Spark SQL, streaming, MLlib, and production deployment

Implement comprehensive audit logging for all admin actions, capturing user ID, action type, entity changes, IP address, and user agent. Use when tracking system activities or adding audit trails.

Analyzes bear-put-spread debit spreads for bearish directional plays with defined risk. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting moderate price decline, comparing put spread configurations, analyzing debit spread opportunities, or evaluating defined-risk bearish positions on mid to large-cap stocks.

Price fixed income securities using present value, yield-to-maturity, and market conventions. Handles treasuries, corporates, municipals with various coupon frequencies. Requires numpy>=1.24.0, pandas>=2.0.0, scipy>=1.10.0. Use when valuing bonds, calculating accrued interest, or analyzing price sensitivity to yield changes.

Analyze personal or business expenses from CSV/Excel. Categorize spending, identify trends, compare periods, and get savings recommendations.

Analyzes bull-call-spread debit spreads for bullish directional plays with defined risk. Requires numpy>=1.24.0, pandas>=2.0.0, matplotlib>=3.7.0, scipy>=1.10.0. Use when expecting moderate price increase, comparing vertical spread configurations, analyzing debit spread opportunities, calculating Greeks for multi-leg positions, or evaluating defined-risk bullish strategies on liquid optionable securities.

This skill provides systematic fact-checking, source verification, and quality assurance methodologies for competitive research deliverables. It works as a companion to the competitive-research-bright

Use when creating maps, working with geographic projections, or processing GeoJSON data. Invoke for world maps, choropleth maps, projection types, geo path generators, spherical geometry, or geographic feature manipulation.

data-analyst-export

Use this skill when the user needs to analyze, clean, or prepare datasets. Helps with listing columns, detecting data types (text, categorical, ordinal, numeric), identifying data quality issues, and cleaning values that don't fit expected patterns. Invoke when users mention data cleaning, data quality, column analysis, type detection, or preparing datasets.

Clean and standardize vehicle insurance data following established business rules.

Data cleaning, preprocessing, and quality assurance techniques

Process JSON with jq and YAML/TOML with yq. Filter, transform, query structured data efficiently. Triggers on: parse JSON, extract from YAML, query config, Docker Compose, K8s manifests, GitHub Actions workflows, package.json, filter data.

Documentation of available data science libraries (scipy, numpy, pandas, sklearn) and best practices for statistical analysis, regression modeling, and organizing analysis scripts. **CRITICAL:** All analysis scripts MUST be placed in reports/{topic}/scripts/, NOT in root scripts/ directory.

This skill should be used when reading any tabular data file (Excel, CSV, Parquet, ODS). It automatically detects and fixes common data issues including multi-level headers, encoding problems, empty rows/columns, and data type mismatches. Returns a clean DataFrame ready for analysis with zero user intervention.

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

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

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.

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.

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.