ds-review
REQUIRED Phase 4 of /ds workflow. Reviews methodology, data quality, and statistical validity.
exploratory-data-analysis
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.
dataset-comparer
Compare two datasets to find differences, added/removed rows, changed values. Use for data validation, ETL verification, or tracking changes.
json-schema-validator
Validate JSON data against JSON Schema specifications. Use for API validation, config file validation, or data quality checks.
data-cleaning
Data cleaning, preprocessing, and quality assurance techniques
office:crm-management
Manage contacts, companies, deals, and relationships. Use when adding contacts, logging interactions, or working with CRM data to prevent duplicates and maintain data quality.
data-validator
Validate data against schemas, business rules, and data quality standards.
