code-review-assistant
Activates when reviewing code to identify quality issues, security vulnerabilities, and suggest improvements
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Activates when reviewing code to identify quality issues, security vulnerabilities, and suggest improvements
Generate comprehensive PySpark-based data quality validation tests for Databricks tables. Use when creating automated tests for data completeness, accuracy, consistency, and conformity, or when user mentions te...
Create and manage Databricks notebooks programmatically. Use when generating ingestion code, creating ETL notebooks, executing Databricks workflows, or when user mentions notebook creation, job automation, or d...
Activates when creating or improving technical documentation, READMEs, and API docs
Manage Unity Catalog metadata tags for data governance and classification. Use when applying tags to tables and columns, classifying data sensitivity (PII, PHI), marking data quality attributes, or when user me...
A clear description of when this skill should activate and what it does
Execute SQL queries against Databricks using the DBSQL MCP server. Use when querying Unity Catalog tables, running SQL analytics, exploring Databricks data, or when user mentions Databricks queries, SQL executi...
Profile datasets to understand schema, quality, and characteristics. Use when analyzing data files (CSV, JSON, Parquet), discovering dataset properties, assessing data quality, or when user mentions data profil...
Connect to and interact with Azure Blob Storage (ADLS Gen2). Use when working with Azure blob storage, listing containers, reading files, uploading data, or when user mentions Azure storage, blob containers, or...
Activates when generating unit tests, integration tests, or test cases for code
Le classement utilise les étoiles du dépôt GitHub indexé. Plusieurs skills peuvent partager ce nombre : ce n’est ni un nombre d’installations ni une note de qualité.