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How to check dashboard YAML for errors before merging with DBT Charts

Run strict validation on board files in a pull request, with no warehouse needed.

Who it is forAn analytics engineer reviewing dashboard changes, or a team lead who wants board files checked the same way as code.

The problemDashboard changes written by people or agents are hard to audit by eye, and errors surface late.

The outcomeA clear pass or fail on every board under charts/, with warnings treated as failures when strict mode is on.

What you need first

  • Python 3.11 to 3.13
  • uv (or pip) to install the dbt-charts package
  • A warehouse adapter extra such as dbt-charts[snowflake] or dbt-charts[bigquery] if you want to run queries against your own warehouse
  • Warehouse credentials for your own data, or the Playground demo data at play.dbtcharts.com

Steps

  1. Run uv tool install dbt-charts on the machine that runs your checks.
  2. Run dct validate charts/guide.yml on one board to confirm the setup works.
  3. Run dct validate --strict to check every board under charts/ and fail on warnings. (inferred, check the README)
  4. Add the same command to your review or CI step so each change is checked before merge.

Prompt for your agent

In the dbt-charts repo, run `dct validate --strict` on the boards changed in <placeholder> and list every error and warning with its file path. Verify that the command exits cleanly once the issues are fixed.

Caveat. The README describes validation as checking board YAML only, so it does not confirm that the SQL returns correct data from your warehouse.

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