Introduction

This cookbook shows how to use Chicory AI agents to improve pipeline efficiency.

Tools & Integrations

• BigQuery – SQL execution and runtime insights

• dbt – Models and transformations

• Airflow – DAG orchestration and pipeline lineage

• DataHub / Redash – Metadata and dashboards

• GitHub – Source control & pull request workflow

• REST API – Deployment mechanism for Chicory agents

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Problem: Cloud data warehouse queries and models often create inefficiencies. Without a comprehensive review of the entire data lakehouse environment, it becomes difficult to understand the broader impact that a proposed change may have on the system.

Quick Start

1. Copy the GitHub Action into your repo.

11KB

pr-analysis.yml

Open

1. Add your Chicory API secrets:

   • CHICORY_API_TOKEN

   • CHICORY_AGENT_ID

2. Open a pull request with changes to your models or SQL code.

3. Chicory AI will analyze the changes and post a performance review comment.