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Validate Project

Validate local Lightdash YAML configurations against remote project content.

3|Updated Feb 13, 2026
Search Tags:#validation#cli#data quality#dbt#semantic layer#lightdash
One-click install
npx skills add https://github.com/yu-iskw/dbt-heros --skill validate-project
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: Validate Project
Source: https://github.com/yu-iskw/dbt-heros/tree/main/plugins/lightdash-development/skills/validate-project
Command: npx skills add https://github.com/yu-iskw/dbt-heros --skill validate-project

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill prevents broken charts and dashboards by validating local semantic layer changes against the remote Lightdash project before deployment.

Core Features & Use Cases

  • Local Validation: Run lightdash validate to check for inconsistencies between your local configurations and the production environment.
  • Targeted Checks: Use --select flags to focus validation on specific models or entities.
  • Use Case: After renaming a dbt model that underlies several Lightdash charts, use this Skill to confirm that none of those charts will break due to the change.

Quick Start

Run lightdash validate to check your local project against the remote configuration.

Frequently Asked Questions about Validate Project

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

FAQPage Schema
How do I validate local dbt model changes against a remote Lightdash project?▼

To validate local dbt model changes against a remote Lightdash project, run the `lightdash validate` command to compare local YAML configurations with production content and identify broken charts or dashboards before deployment.

What is Lightdash semantic layer validation and when do I need it?▼

Lightdash semantic layer validation is a consistency check that compares local configurations against remote project content. You need it after modifying dbt models to proactively prevent broken charts or dashboards in production.

Do I need the Lightdash CLI installed to check for broken charts?▼

Yes, you need the Lightdash CLI installed and configured for your target project to check for broken charts. The CLI runs the validation process that detects inconsistencies between local YAML files and remote visualization content.

Can I run Lightdash validation checks on specific dbt models or entities?▼

Yes, you can run validation checks on specific dbt models or entities by using the `--select` flag with the `lightdash validate` command. This targets the validation scope to focus only on the selected components.

What's the best way to prevent broken Lightdash dashboards after renaming a dbt model?▼

The best way to prevent broken Lightdash dashboards after renaming a dbt model is to run a local validation check using the Lightdash CLI. This compares your local YAML configurations against the remote project to confirm no charts will break.

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