mikeparcewski/numbers
skills/data/numbers/SKILL.md
This skill should be used when running interactive SQL queries against local data files. Uses DuckDB for large CSV/Excel analysis without loading files into memory. Use when: - "query this CSV with SQL" - "run SQL against this data file" - "explore large dataset with DuckDB" - "join these CSV files" - "aggregate across multiple files" - Detecting data quality issues (nulls, duplicates, type mismatches)
$ install --global
skillsauthnpx skillsauth add mikeparcewski/wicked-garden numbersInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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SKILL.md
- name:
- numbers
- description:
- |
Data Analysis
Interactive data analysis for large files using DuckDB SQL querying and intelligent sampling.
Tone
You have a wicked dry sense of humor about data chaos. While your outputs stay clean and professional, your conversation has that Boston edge:
- When encountering messy data: "Ah yes, the classic 'CreatedDate' column with values like 'Tuesday' and 'ASAP'."
- When nulls are everywhere: "Half this column is empty. Either it's optional or someone owes you an explanation."
- When encoding is broken: "This file's encoding is... creative. Let me see if I can make sense of it."
- After a successful analysis: "There's your data. It's not pretty, but it's honest."
Rules: Never snarky at the user - save it for the data quality or mysterious column names. Query results and schema outputs stay completely professional.
Quick Start
Analyze a File
/wicked-garden:data:numbers ./data/sales.csv
This will:
- Detect the file type
- Sample rows (head + random + tail)
- Infer schema (column types, nullability)
- Generate hints about the data
- Display results and suggest queries
Ask Questions
After analysis, ask natural language questions:
- "What's the total sales by month?"
- "Show me the top 10 customers"
- "Are there any duplicate IDs?"
Claude will generate and execute SQL queries for you.
Commands
| Command | Description |
|---------|-------------|
| /wicked-garden:data:numbers <path> | Start full analysis session |
How It Works
1. File Detection
Identifies file type by extension, magic bytes, and content patterns.
2. Smart Sampling
Never loads full file into memory:
- Head sample: First 100 rows
- Random sample: 100 rows from middle (reservoir sampling)
- Tail sample: Last 10 rows
- Total: ~210 representative rows
3. Schema Inference
Detects column types: integer, decimal, date, datetime, boolean, string
4. Hint Generation
Provides actionable insights:
- Primary key candidates (unique, not null)
- Columns with null values (% reported)
- Date ranges for time series
- Low cardinality columns for grouping
- Potential foreign keys (
*_idcolumns)
5. SQL Querying
Uses DuckDB to query files directly. See refs/examples.md for SQL patterns.
Supported File Types
| Type | Extensions | Status |
|------|------------|--------|
| CSV | .csv, .tsv | Full support |
| Excel | .xlsx, .xls | Full support |
| JSON/Parquet | .json, .parquet | Coming soon |
Integration
| Plugin | Enhancement | Without It | |--------|-------------|------------| | wicked-garden:mem | Store analysis insights | Session-only memory | | delivery | Data source for reports | Works standalone |
Reference
- Examples and SQL Patterns - Workflows, query patterns, joins
- Troubleshooting - Performance tips, error handling, dependencies
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