dct

Use this skill when the user wants to visualize data distributions, create ASCII histograms, generate simple charts from CSV/JSON data, plot column values, or see value frequencies in terminal-friendly format. Triggers include "chart this data", "visualize distribution", "histogram of values", "plot the data", "ascii chart", "terminal visualization", or when needing quick visual analysis without external plotting tools.

Use this skill when the user wants to compare two data files, find differences between datasets, validate data consistency, check if files have matching records, or reconcile data between sources. Triggers include "compare these files", "diff the datasets", "are these the same", "find differences", "validate data matches", "reconcile", "data comparison", or when doing data quality validation between two files.

Use this skill when the user wants to flatten nested JSON structures, convert nested objects to flat format, generate SQL queries from nested JSON, unnest hierarchical data, or work with nested API responses that need to be tabular. Triggers include "flatten this json", "make json flat", "nested to flat", "unnest json", "json to sql", "flatten nested", or when dealing with deeply nested JSON from APIs or document stores.

Use this skill when the user wants to create synthetic test data, generate fake datasets, create mock data for testing, produce realistic data with specific patterns, or need sample data with custom schemas. Triggers include "generate test data", "create fake data", "mock dataset", "synthetic data", "generate sample records", "create test data", "fake users", "mock data", or when needing test data with specific fields and relationships.

Use this skill when the user wants to generate SQL CREATE TABLE statements from data files, infer schema from CSV/JSON/Parquet, create database schemas from existing data, or get column types from a file. Triggers include "generate schema", "create table from csv", "infer types", "what's the schema", "get column types", "sql ddl", or when preparing data for SQL databases like DuckDB, PostgreSQL, or similar.

Use this skill when the user wants to convert JSON Schema to SQL CREATE TABLE statements, transform schema definitions to database DDL, create SQL tables from JSON Schema files, or generate database schemas from API specifications. Triggers include "json schema to sql", "convert schema to sql", "create table from json schema", "json schema ddl", "schema conversion", or when working with OpenAPI, JSON Schema, or API specifications that need database tables.

Use this skill when the user wants to preview or inspect the contents of a data file (CSV, JSON, NDJSON, Parquet). Triggers include "show me the data", "preview this file", "what's in this csv", "look at the first rows", "sample the data", or when needing to understand data structure before processing. This is often the first step before other data operations.

Use this skill when the user wants to analyze data quality, profile data files, check value distributions, perform character analysis on text fields, identify data quality issues, or get statistics about dataset contents. Triggers include "profile this data", "analyze data quality", "check for nulls", "value distribution", "character frequency", "data statistics", "column profiling", or when doing exploratory data analysis or quality assessment.

Router skill for DCT (Data Check Tool). Use this skill whenever the user wants to work with flat data files (CSV, JSON, NDJSON, Parquet) for inspection, comparison, transformation, or generation. The main dct skill analyzes user intent and routes to appropriate sub-skills. Triggers include any mention of data files, previewing data, comparing datasets, generating test data, flattening JSON, creating SQL schemas, profiling data, or visualizing distributions.