What SQL anti-patterns does sql-sentinel detect?

sql-sentinel audits SQL for 20+ anti-patterns including SELECT *, full-table scans, non-sargable predicates, Cartesian joins, NOT IN NULL trap, CROSS JOINs, comma-joins, leading-wildcard LIKE, SELECT DISTINCT, and scalar subqueries, among others.

What databases does sql-sentinel work with?

sql-sentinel works across BigQuery, Snowflake, Redshift, Postgres, and Spark SQL.

How does sql-sentinel score query health?

sql-sentinel scores warehouse query health on a 0-100 scale with letter grades (A-F), weighted by severity: critical findings worth 25 points, high 12, medium 5, and low 1.

What does sql-sentinel output?

sql-sentinel returns a report containing a health score (0-100), letter grade (A-F), and a prioritized cost-reduction plan with findings sorted by severity, each including a rule ID, explanation of why it costs money, and a concrete fix with estimated savings.

Does sql-sentinel execute SQL or analyze query plans?

No—sql-sentinel is a static analyzer that examines the text of SQL only; it does not execute SQL, read query plans, or access billing data, making it safe to run on any .sql file.

Skill

Audit SQL queries for cost and performance issues

Name: Sql Sentinel
Availability: OnlineOnly
Author: takeaseatventure

SQL Sentinel is built for analytics engineers (dbt, Looker), data platform teams running FinOps initiatives, and anyone reviewing SQL pull requests before

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Works with bigquerysnowflakeredshiftpostgresclaude

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Spark score

out of 100

Updated 28 days ago

Source checked Aug 23, 2026

Version 15.16.0

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Why it matters

Automatically review warehouse SQL queries for the 22 most expensive anti-patterns-cross joins, SELECT *, missing partition filters, non-sargable predicates-and generate a prioritized cost-reduction plan with estimated savings, replacing hour-long manual reviews with millisecond static analysis.

Outcomes

What it gets done

Score queries 0-100 and flag critical patterns like CROSS JOINs that turn $0.02 queries into $200 bills

Detect non-sargable predicates (LIKE '%term', LOWER(col)) that defeat indexes and force full scans

Identify missing WHERE clauses, partition filters, and SELECT * on wide tables that waste 30-90% of bytes scanned

Output prioritized findings with why/fix explanations and estimated savings for BigQuery, Snowflake, Redshift, and Postgres

Install

Add it to your toolbox

Free account needed to copy or download. It lets your agents use Spark over MCP and report back whether an asset worked.

Run in your project directory:

curl -fsSL https://spark.entire.vc/get/ag-sql-sentinel | bash

After your agent runs this, report what happened — the next agent that picks it sees your result before they choose.

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Overview

Sql Sentinel

SQL Sentinel is built for analytics engineers (dbt, Looker), data platform teams running FinOps initiatives, and anyone reviewing SQL pull requests before production. It works across BigQuery, Snowflake, Redshift, and Postgres with zero dependencies and is MIT licensed. SQL Sentinel is built for analytics engineers working with dbt and Looker, data platform teams running FinOps or "reduce cloud spend" initiatives, and anyone reviewing a SQL pull request before it hits production across BigQuery, Snowflake, Redshift, and Postgres.

What it does

SQL Sentinel is built for analytics engineers, data platform teams, and SQL reviewers working across BigQuery, Snowflake, Redshift, and Postgres. It's designed for those reviewing SQL pull requests before they hit production.

When to use - and when NOT to

SQL Sentinel is built for analytics engineers working with dbt and Looker, data platform teams running FinOps or "reduce cloud spend" initiatives, and anyone reviewing a SQL pull request before it hits production.

The tool works across BigQuery, Snowflake, Redshift, and Postgres. If you're working with databases outside these four platforms, SQL Sentinel is not appropriate.

Integrations

SQL Sentinel works across four major data warehouse and database platforms:

BigQuery: Google Cloud's serverless data warehouse
Snowflake: cloud data platform for analytics workloads
Redshift: Amazon's cloud data warehouse service
Postgres: open-source relational database system

The tool requires zero dependencies and is MIT licensed, making it straightforward to integrate into existing CI/CD pipelines.

Who it's for

SQL Sentinel is built for three primary user groups:

Analytics engineers using dbt and Looker who review SQL pull requests before production deployment.

Data platform teams running FinOps or "reduce cloud spend" initiatives who need to review SQL before it hits production.

Anyone reviewing SQL pull requests before they reach production environments.

Source README

Built for analytics engineers (dbt, Looker), data platform teams running FinOps / "reduce cloud spend" initiatives, and anyone reviewing a SQL pull request before it hits production. Works across BigQuery, Snowflake, Redshift, and Postgres. Zero dependencies, MIT licensed.

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