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dbt Wizard config reference Beta

dbt Wizard stores configuration in two TOML files under ~/.dbt/wizard/, each controlling a different part of the product.

The two config files

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We'd love to hear how dbt Wizard is working for you. Share your feedback by either running the /feedback slash command in your interactive terminal session or by going to the #dbt-wizard channel in the dbt Community Slack.

Thanks so much for your help in improving dbt Wizard and dbt data development!

TOML (Tom's Obvious, Minimal Language) is a config file format. If you've written YAML or JSON before, it'll feel familiar — keys and values are separated by = (with spaces before and after the equals sign), and nested sections use [section.name] headers instead of indentation or curly braces. For example:

~/.dbt/wizard/config.toml
model = "claude-sonnet-4-6"

[projects."/Users/you/jaffle-shop"]
trust_level = "trusted"

This config sets the default AI model for all new sessions and applies to all future invocations across all projects. You can override the default AI model for a specific project by setting the model key in the wizard_config.toml file for that project or using the /model picker in the text-based user interface (TUI).

FileControlsWhen to use
~/.dbt/wizard/config.tomlAgent runtime — AI model, MCP servers, approval rules, trusted projectsChange agent-level behavior across all sessions
~/.dbt/wizard/wizard_config.tomlPer-project settings — dbt executable path, deferral, saved model preferenceChange how dbt Wizard works with a specific dbt project

Note that dbt_project.yml is separate from both and controls how dbt builds your project.

Common tasks

GoalEditRestart needed?
Change the default AI modelconfig.tomlmodel = "claude-sonnet-4-6"Yes
Point dbt Wizard at a specific dbt binarywizard_config.tomlpathYes
Add the dbt MCP serverconfig.toml[mcp_servers.dbt]Yes
Mark a repo as trustedconfig.tomltrust_level = "trusted" under [projects."..."]Yes
Change approval or sandbox defaultsconfig.tomlYes

Config precedence

Settings resolve in this order (highest to lowest):

  1. CLI flags (-m, -c) at invocation
  2. In-session model picker (/model)
  3. ~/.dbt/wizard/config.toml
  4. ~/.dbt/wizard/wizard_config.toml
  5. Built-in defaults

config.toml

Global agent settings for models, approvals, sandboxing, web search, and MCP servers.

~/.dbt/wizard/config.toml controls how the agent session behaves. It's created automatically when dbt Wizard is installed.

Configuration keys

This is the list of configuration keys that can be set in config.toml.

  • model
  • approval_policy
  • sandbox_mode
  • web_search

You can view more by running wizard config --help.

AI model and API

KeyTypeDefaultDescription
modelstringDefault AI model for new sessions. Refer to AI model ID format below. Change interactively with /model in the TUI.

Behavior

KeyTypeDefaultDescription
approval_policystringon-requestWhen Wizard asks before executing commands. Options: untrusted (ask for non-trusted commands), on-request (dbt Wizard decides), never (run without asking).
sandbox_modestringread-onlyShell sandbox policy. Options: read-only (default), workspace-write (allow writes inside project dir), danger-full-access (no restrictions).
web_searchstringcachedWeb search mode. Options: disabled, cached, or live.

Project trust

Set trust_level per-project to allow dbt Wizard to use project-local config:

[projects."/absolute/path/to/your-repo"]
trust_level = "trusted"

MCP servers

[mcp_servers.dbt]
command = "DBT_MCP_ENDPOINT"

AI model ID format

AI model IDs in config.toml use the public model ID, such as claude-sonnet-4-6.

To list all available AI model IDs:

wizard debug models

Environment variables

Any key can be set as an environment variable using the DBT_WIZARD_ prefix in SCREAMING_SNAKE_CASE:

export DBT_WIZARD_MODEL=claude-sonnet-4-6
export DBT_WIZARD_APPROVAL_POLICY=never
export OPENAI_API_KEY=sk-... # OpenAI (no prefix needed)
export ANTHROPIC_API_KEY=sk-ant-... # Anthropic (no prefix needed)

OPENAI_API_KEY and ANTHROPIC_API_KEY are read directly without the DBT_WIZARD_ prefix, following each provider's convention.

When it's read

config.toml is read at session start when you run wizard. Changes take effect only after you exit and restart the CLI. Per-invocation -c flags and the in-session /model picker override this file for that session only.

Example

model = "claude-sonnet-4-6"

[projects."/Users/you/jaffle-shop"]
trust_level = "trusted"

[mcp_servers.dbt]
command = "DBT_MCP_ENDPOINT"

wizard_config.toml

Per-project settings Wizard writes during onboarding, including dbt path and deferral settings.

~/.dbt/wizard/wizard_config.toml stores what dbt Wizard knows about each of your dbt projects. dbt Wizard writes to this file automatically during onboarding and when you change project settings. You can also edit it manually.

Configuration keys

KeyDescription
versionSchema version for this file (currently 1). Don't change this manually.
global.terms_of_use_accepted_atTimestamp of when you accepted the dbt Wizard Terms of Use. Written once under the [global] section and applies across all projects.
onboarded_atTimestamp of when you onboarded this project in dbt Wizard.
pathPath to the dbt binary dbt Wizard should use for this project.
deferral.modeWho handles deferral for this project. "wizard" means dbt Wizard handles it — you tell it which profiles.yml target to defer to, and it reuses that target's models instead of rebuilding everything. "fusion_cloud" means the dbt platform handles deferral against your connected environment. Refer to Deferral below.
deferral.targetThe target from your profiles.yml that dbt Wizard compiles and defers to when deferral.mode is "wizard" (for example, "dev").

Settings are stored per-project under [projects."/absolute/path/to/repo"] blocks:

~/.dbt/wizard/wizard_config.toml
version = 1

[global]
terms_of_use_accepted_at = "2026-05-28T15:06:54Z"

[projects."/Users/you/jaffle-shop"]
onboarded_at = "2026-05-20T11:09:01.410346"
path = "/Users/you/jaffle-shop/.venv/bin/dbt"

[projects."/Users/you/jaffle-shop".deferral]
mode = "wizard"
target = "dev"

Deferral

Deferral lets dbt Wizard reuse models that are already built elsewhere (for example, in production) instead of rebuilding everything when you're only working on part of a project, saving you time and warehouse cost.

The deferral.mode setting in wizard_config.toml controls who handles deferral. It accepts five values, and dbt Wizard usually sets it for you during onboarding:

deferral.mode valueWhat it means
"wizard"dbt Wizard handles deferral for you. You tell dbt Wizard which target from your profiles.yml to defer to (it tries to detect one automatically when you first set up the project). dbt Wizard then compiles that target and reuses its models for any upstream models you haven't built yourself.
"fusion_cloud"The dbt platform handles deferral against your connected environment, so dbt Wizard doesn't manage any local state. Set automatically when you're connected to the platform.
"dbt-state"dbt state handles deferral, so dbt Wizard skips its own production compile.
"manual"You maintain the deferral manifest path manually.
"disabled"Deferral is disabled for the project.

For more about dbt State, refer to About dbt State.

About favor-state: favor-state is a built-in dbt deferral option, not something you need to configure here — dbt Wizard handles it for you during deferral compiles. You don't need to add favor_state to wizard_config.toml. What matters instead is that dbt Wizard uses a valid deferral mode and state path.

In practice, when dbt Wizard handles deferral it uses your own dev version of a model when you've already built one, and only falls back to the version from the deferred target for models you haven't built yet.

For how this behaves during a session, refer to Deferral and state.

Troubleshooting

Here are some common config mistakes and how to fix them:

SymptomLikely causeFix
Still on old AI model after editing wizard_config.tomlwizard_config.toml doesn't store the modelSet model in config.toml and restart wizard
AI model unchanged after editing config.tomlOld session still runningPress Ctrl+C, then run wizard again
"Invalid model" errorWrong AI model IDRun wizard debug models to see valid AI model IDs

Re-trigger onboarding flows

If you need to re-run part of the setup — for example, after deleting config entries by mistake or switching to a new project — you can reset individual flows by deleting the relevant file. dbt Wizard will re-prompt you the next time it runs.

To delete a file, run the command in your terminal (macOS/Linux). For example:

rm ~/.dbt/wizard/auth.json

If you get a No such file or directory error, the file doesn't exist — which means that part of the setup hasn't run yet, or has already been reset. You can ignore the error.

What you want to redoFile to delete
Re-run the trusted folder promptRemove your project's entry from ~/.dbt/wizard/config.toml under [projects."..."]
Re-authenticate with dbt platform~/.dbt/wizard/auth.json
Re-run dbt project setupRemove your project's entry from ~/.dbt/wizard/wizard_config.toml under [projects."..."], or delete the file entirely to reset all projects
Re-trigger BYOK key configuration~/.dbt/wizard/provider* (this matches all provider files)
caution

config.toml and wizard_config.toml are separate files that control different things. If you want to re-run project setup, edit wizard_config.toml — not config.toml. Editing the wrong file won't re-run the onboarding flow you expect. Refer to The two config files at the top of this page for the difference.

Links to BYOK setup, approval behavior, and CLI command reference.

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