Analyze messy multi-format data and generate validated reports with charts.
npx skills add https://github.com/SpaceZephyr/myskill --skill data-analysis-spacezephyr
Please help me install this Agent Skill. Skill: data-analysis Source: https://github.com/SpaceZephyr/myskill/tree/main/data-analysis Command: npx skills add https://github.com/SpaceZephyr/myskill --skill data-analysis-spacezephyr
This Skill helps you safely analyze messy, multi-format data without loading everything into context, so you can avoid token overflow, detect data quality issues early, and produce reliable findings.
Analyze the attached dataset, inspect its structure and quality, then generate a concise Markdown report with key findings and charts.
High-intent search queries and answers about installing and using this skill.
Exploratory data analysis on messy CSV and Excel files is performed by safely sampling data, inspecting metadata, and running quality checks for missing values and duplicates before generating validated insights, charts, and structured Markdown reports.
Analyzing data across PDF and DOCX sources involves cross-file extraction and safe sampling to avoid token overflow, applying quality validation, and producing consolidated business reporting with visualizations.
Yes, Python and pandas are used for data quality checks and visualization, applying type issue detection, range error identification, and consistency problem checks before delivering validated reports.
Data visualization and reporting supports image-based data sources alongside CSV, Excel, PDF, DOCX, and Markdown, applying metadata inspection and sampling to handle multi-format messy data safely without loading everything into context.
Analyzing large multi-format datasets causes token overflow by loading everything into context, which is avoided by applying safe sampling, metadata inspection, and small data extraction before running Python-based cleaning and analysis.
Generating structured business reports from raw data findings is done by performing statistical analysis and pattern discovery, then exporting the validated insights into Markdown, PDF, or DOCX report formats with embedded charts.
takusaotomeConvert DOCX, PPTX, HTML, Markdown, and images into optimized PDFs.
zephyrwang6Analyze raw tables, documents, and images into validated Markdown, PDF, or DOCX reports.
0xMerl99Analyze datasets with pandas, numpy, matplotlib, and seaborn for EDA, cleaning, statistics, and visualizations.
kardelitaituRead and analyze local text, PDF, DOCX, Excel, and image files.
