dialect-bigquery

Name: dialect-bigquery
Availability: InStock
Author: Mako

Write and debug BigQuery SQL with backtick identifiers, SAFE_CAST, and FORMAT_DATE.

11|6|Updated Nov 15, 2025

Search Tags:#sql #bigquery #dialect #backtick-identifiers #format_date #regexp_contains

Ready to run

npx skills add https://github.com/mako-ai/mako --skill dialect-bigquery

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: dialect-bigquery
Source: https://github.com/mako-ai/mako/tree/main/api/src/agent-skills/dialect-bigquery
Command: npx skills add https://github.com/mako-ai/mako --skill dialect-bigquery

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

BigQuery SQL often requires precise identifiers, safe casting, and specialized functions. This dialect helps you write and debug SQL for BigQuery by guiding the correct use of backtick-quoted identifiers, casts, and BigQuery-specific functions.

Core Features & Use Cases

Backtick-qualified identifiers: Use project.dataset.table notation to avoid ambiguity in multi-project environments.
Type handling: Employ CAST and SAFE_CAST to manage data types safely and predictably.
BigQuery functions: Utilize REGEXP_CONTAINS, FORMAT_DATE, and UNNEST for nested and repeated fields.
Use Case: Build robust queries for dashboards and data pipelines that rely on precise date formatting and safe casting.

Quick Start

Write a BigQuery SQL query that selects from a fully-qualified table like my_project.my_dataset.orders and formats order_date with FORMAT_DATE.

Frequently Asked Questions about dialect-bigquery

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I write BigQuery SQL with backtick-quoted identifiers for fully-qualified tables?▼

To write BigQuery SQL with backtick-quoted identifiers, enclose project, dataset, and table names in backticks like `project.dataset.table`. This prevents ambiguity in multi-project environments and ensures reliable query execution.

What is the best way to format dates in BigQuery SQL?▼

The best way to format dates in BigQuery SQL is using the FORMAT_DATE function. This specialized function allows you to parse and structure date values precisely for dashboards and data pipelines.

Why does my BigQuery SQL fail when handling nested or repeated fields?▼

BigQuery SQL fails on nested or repeated fields when they are not properly flattened. You must use the UNNEST function to expand arrays and structs, allowing you to query individual records within nested fields reliably.

Can I use SAFE_CAST to manage data types safely in BigQuery?▼

Yes, you can use SAFE_CAST to manage data types safely in BigQuery. It converts values to the specified type and returns NULL instead of raising an error when the cast fails, ensuring predictable data pipelines.

How do I use REGEXP_CONTAINS for pattern matching in BigQuery SQL?▼

To use REGEXP_CONTAINS in BigQuery SQL, pass a target string and a regular expression pattern to the function. It returns a boolean indicating if the pattern exists within the string, which is ideal for filtering data.

Does dialect-bigquery work for building data pipelines and dashboards?▼

Yes, dialect-bigquery works for building data pipelines and dashboards. It guides the correct usage of BigQuery-specific functions, safe casting, and precise date formatting required for robust, reliable analytical outputs.