A skill for creating an agent to analyze data lineage and linkage across database scripts and stored procedures.
Profiles CSV and spreadsheet exports before you trust them: infers column types and measures missing values, duplicates, mixed types, outliers, date format chaos, and key uniqueness with a tested Python script, then writes a prioritized data quality report with safe fixes.
This skill allows you to interact with Trello account to list boards, view lists, and create cards automatically.
Reviews PostgreSQL and MySQL tables (schema.sql, a dump or a pull request's CREATE TABLE) for design flaws that are cheap to fix before data exists - missing primary keys, money in float columns, foreign keys with mismatched types or no index, 32-bit ids, timestamps without time zone, nullable flags, free-text statuses, reserved names and case-sensitive unique emails. Returns corrected DDL. Includes a stdlib Python linter with --self-test.
Reviews SQL queries and optional EXPLAIN output for common performance problems such as SELECT *, functions or casts on indexed columns, leading-wildcard LIKE, N+1 query loops, OR across columns vs UNION ALL, AND/OR precedence slips, NOT IN subqueries, deep OFFSET paging, seq scans and disk sorts. Explains each problem and gives a rewritten query. Includes a stdlib Python checker with --self-test.
