Convert natural-language requests into executable DuckDB SQL queries.
npx skills add https://github.com/nq-rdl/agent-extensions --skill query-nq-rdl
Please help me install this Agent Skill. Skill: query Source: https://github.com/nq-rdl/agent-extensions/tree/main/skills/duckdb/query Command: npx skills add https://github.com/nq-rdl/agent-extensions --skill query-nq-rdl
This Skill enables you to execute SQL queries against an attached DuckDB database or directly against local data files, supporting natural-language requests that require SQL generation.
Ask the AI to run a SQL query against your DuckDB database or a local data file.
High-intent search queries and answers about installing and using this skill.
To query a local data file using natural language, you can submit your request directly to the system. It generates schema-aware DuckDB SQL from your text, executes it against the file-backed data, and returns the results.
Yes, you can run ad-hoc SQL queries against an in-memory DuckDB database. The system determines ad-hoc versus session mode based on your state and data references, executing your SQL directly with safety checks.
This approach supports both raw SQL execution and natural-language query (NLQ) to SQL generation. It treats your input as either direct SQL or natural language, generating executable DuckDB queries with schema awareness.
The best way to execute SQL on local data files without a full database setup is using DuckDB. This system processes file-backed datasets directly, handling query generation, execution, and result management with built-in safety checks.
A key limitation when generating SQL from natural language for data analysis is result size and safety. The system enforces safety checks and provides guidance on result size to manage large outputs from your generated DuckDB queries.
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