DCT (Data Check Tool) - Skill Router
DCT is a Swiss army knife CLI tool for working with flat data files. This skill routes to appropriate sub-skills based on user intent.
Quick Command Reference
| User Intent |
Route To |
Command Pattern |
| Preview/inspect data |
dct-peek |
dct peek <file> |
| Generate SQL schema |
dct-infer |
dct infer <file> |
| Compare two datasets |
dct-diff |
dct diff <keys> <file1> <file2> |
| Generate synthetic data |
dct-generate |
dct gen <schema> |
| Flatten nested JSON |
dct-flattify |
dct flattify <json> |
| Analyze data quality |
dct-profile |
dct prof <file> |
| JSON Schema to SQL |
dct-js2sql |
dct js2sql <schema> |
| Visualize data |
dct-chart |
dct chart <file> <col> |
Routing Logic
Analyze the user's request and route to the appropriate sub-skill:
Route to dct-peek when:
- User wants to preview data files
- Keywords: "peek", "preview", "show me", "look at", "first rows", "sample"
- Example: "Show me the first 10 rows of data.csv"
Route to dct-infer when:
- User wants to generate SQL schemas
- Keywords: "infer", "schema", "create table", "sql from data", "ddl"
- Example: "Generate a CREATE TABLE statement from this CSV"
Route to dct-diff when:
- User wants to compare two files
- Keywords: "diff", "compare", "differences", "match", "reconcile", "validate"
- Example: "Compare these two CSV files by the ID column"
Route to dct-generate when:
- User wants to create synthetic test data
- Keywords: "generate", "synthetic", "mock", "fake data", "test data"
- Example: "Generate 1000 fake user records"
Route to dct-flattify when:
- User wants to flatten nested JSON
- Keywords: "flatten", "unnest", "nested json", "make flat"
- Example: "Flatten this nested JSON from the API response"
Route to dct-profile when:
- User wants to analyze data quality
- Keywords: "profile", "analyze", "data quality", "statistics", "distribution"
- Example: "Profile this data file for quality issues"
Route to dct-js2sql when:
- User wants to convert JSON Schema to SQL
- Keywords: "json schema", "convert schema", "schema to sql"
- Example: "Convert this JSON Schema to a CREATE TABLE statement"
Route to dct-chart when:
- User wants to visualize data
- Keywords: "chart", "visualize", "histogram", "plot", "graph"
- Example: "Create a chart of the sales column"
Common Patterns
Data Validation Workflow
dct-peek: Preview to understand structure
dct-profile: Check data quality
dct-infer: Generate schema for downstream use
Data Comparison Workflow
dct-peek: Preview both files
dct-diff: Compare with appropriate keys
Test Data Generation Workflow
dct-generate: Create synthetic data
dct-peek: Verify generated data
dct-diff: Compare with production sample
Installation
All sub-skills require DCT to be installed:
which dct || go build -o dct && chmod +x ./dct
Supported File Formats
All DCT sub-skills support:
- CSV (.csv)
- JSON (.json)
- NDJSON (.ndjson) - newline-delimited JSON
- Parquet (.parquet)
Error Handling
If a sub-skill encounters errors:
- Verify the file exists and is readable
- Check file extension matches content format
- Ensure DCT binary is built and executable