Duckdb

This gives Claude the ability to run SQL queries directly on your data files without spinning up a database server. Point it at CSVs, Parquet files, or JSON and write analytical queries with joins, window functions, and aggregations. It can also query pandas and Polars DataFrames in place, which is genuinely useful when you're neck-deep in a Jupyter notebook and don't want to wrestle with method chaining. The performance is solid for medium to large datasets since it's built for OLAP workloads. Think of it as SQLite's analytical cousin. Best when you need complex SQL on local files or want to join data across different formats without loading everything into memory first.

skills.sh installs: 317
GitHub stars: 3
last updated: Aug 21, 2026

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Install

$ npx -y skills add silvainfm/claude-skills --skill duckdb --agent claude-code

Installs into .claude/skills of the current project.

Files

DuckDB

Overview

DuckDB is a high-performance, in-process analytical database management system (often called "SQLite for analytics"). Execute complex SQL queries directly on CSV, Parquet, JSON files, and Python DataFrames (pandas, Polars) without importing data or running a separate database server.

When to Use This Skill

Activate when the user:

Wants to run SQL queries on data files (CSV, Parquet, JSON)
Needs to perform complex analytical queries (aggregations, joins, window functions)
Asks to query pandas or Polars DataFrames using SQL
Wants to explore or analyze data without loading it into memory
Needs fast analytical performance on medium to large datasets
Mentions DuckDB explicitly or wants OLAP-style analytics

Installation

Check if DuckDB is installed:

python3 -c "import duckdb; print(duckdb.__version__)"

If not installed:

pip3 install duckdb

For Polars integration:

pip3 install duckdb 'polars[pyarrow]'

Core Capabilities

1. Querying Data Files Directly

DuckDB can query files without loading them into memory:

import duckdb

SKILL.md on GitHub

Details

Repository: github.com/silvainfm/claude-skills
Categories: Backend & APIs, Data Science & ML, Python, Marketing & SEO, Databases
First seen: Jun 3, 2026