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What you can do with DBT Charts

dbt Charts is a declarative YAML syntax around SQL for building dashboards, with a dct CLI that validates, previews, renders, and queries board definitions.

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dbt-labs/dbt-charts on GitHub

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What do you want to do?

5 use cases

  • Build a KPI dashboard from warehouse SQL with an agent

    Have a coding agent turn your SQL queries into a validated, live-previewed YAML dashboard.

    View prompt
    Using the dbt-charts repo, install the CLI, run `dct skills intro`, and write a KPI board for the metrics described in <placeholder> as YAML under charts/. Run `dct validate` on the file and report any errors. Verify that the board renders in `dct serve`.

  • Check dashboard YAML for errors before merging

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

    View prompt
    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.

  • Find which dashboards break when a column changes

    Use dct impact to list the boards that reference a column before you rename it.

    View prompt
    In the dbt-charts repo, run `dct impact` for the column <placeholder> and list every board that references it. Verify the list against `dct search` results for the same name.

  • Export a dashboard as HTML, PDF, or PNG

    Render a board to a static file that you can send to people who do not run the CLI.

    View prompt
    In the dbt-charts repo, render the board at <placeholder> to PDF with `dct render <placeholder> --format pdf` and report the output file path. Verify that the file opens and shows the expected charts.

  • Run SQL against your warehouse from the terminal

    Use dct query to test a metric query, or run a named board query, before you build a chart.

    View prompt
    In the dbt-charts repo, run `dct query <placeholder> 'SELECT …'` with the SQL for the metric <placeholder> and print the result rows. Verify that the row count and totals match a known figure from your source system.

How to use DBT Charts

  1. Check you have what it needs: 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.
  2. Open dbt-labs/dbt-charts on GitHub and read the README and license.
  3. Run uv tool install dbt-charts to install the CLI.
  4. Run dct skills intro and follow the printed guidance so the agent knows the board format.
  5. Run dct init to bootstrap a project with charts/guide.yml.
  6. Run dct validate charts/guide.yml to check the board YAML before you preview it.

These steps come from our top use case, Build a KPI dashboard from warehouse SQL with an agent, which also has a copy-paste agent prompt.

DBT Charts alternatives · Best AI repos for Data and analytics

About this repo

  • Who it is forAnalysts, analytics engineers, and data teams who want dashboards defined in reviewable YAML that coding agents can write and humans can audit.
  • Why it is hot
  • LanguagePython
  • Sourcegithub.com/dbt-labs/dbt-charts · Back to Hot repos

Requirements

  • 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
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Questions about DBT Charts

What is DBT Charts?

dbt Charts is a declarative YAML syntax around SQL for building dashboards, with a dct CLI that validates, previews, renders, and queries board definitions. It is an open-source project on GitHub: https://github.com/dbt-labs/dbt-charts.

Who is DBT Charts for?

Analysts, analytics engineers, and data teams who want dashboards defined in reviewable YAML that coding agents can write and humans can audit.

What can I do with DBT Charts?

5 use cases so far, for example: Build a KPI dashboard from warehouse SQL with an agent; Check dashboard YAML for errors before merging; Find which dashboards break when a column changes. Each has steps and a copy-paste agent prompt.

What do I need to run DBT Charts?

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.

What are alternatives to DBT Charts?

Other hot AI repos in Data and analytics: Kronos, Brandpose, Idx, Open Lakehouse Compute Fabric, Zepp Bridge.

Is DBT Charts safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.