Profile tables and columns for statistics, distributions, cardinality via AnacondaArmor API.
npx skills add https://github.com/anomalyarmor/agents --skill armor-profile
Please help me install this Agent Skill. Skill: armor-profile Source: https://github.com/anomalyarmor/agents/tree/main/skills/profile Command: npx skills add https://github.com/anomalyarmor/agents --skill armor-profile
This Skill automates the process of gathering detailed statistics and understanding data distributions for tables and columns, providing insights into data quality and characteristics.
orders table by checking its row count, identifying columns with high null rates, and analyzing the distribution of values in the status column.Use the armor-profile skill to get a summary of metrics for the asset with ID 'asset-uuid'.
High-intent search queries and answers about installing and using this skill.
To analyze table and column statistics, use this Skill to retrieve row counts, null rates, distinct value counts, and value distributions via the AnomalyArmor API. It automates comprehensive data profiling to provide detailed insights into data characteristics and quality.
Data profiling is the process of examining table and column statistics to understand data distributions, cardinality, and null rates. It helps with data quality checks by identifying columns with high null rates and tracking metric changes over time through historical snapshots.
Yes, you need the AnomalyArmor Python SDK to retrieve column statistics. The Skill requires the SDK to interact with the AnomalyArmor API for metric retrieval and creation, enabling automated analysis of null rates, cardinality, and value ranges.
You can track historical trends of data metrics by viewing historical snapshots within the profiling results. This allows you to monitor changes in row counts and column statistics over time to maintain ongoing data quality.
To set up new monitoring metrics, use this Skill to create new checks via the AnomalyArmor API. This supports deeper data analysis workflows by generating detailed insights into specific table and column characteristics beyond the default profiles.
The best way to identify columns with high null rates is to perform column-level statistics profiling. This Skill analyzes null rates, distinct value counts, and value ranges for individual columns, helping you understand the quality of your data assets.
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