Note: The scripts automatically load the environment variables from various .env files. Do not ask the user to set vars unless skill executions fails due to env var absence.

Scripts

add_dashboard_element

This skill creates a new tile (element) within an existing Looker dashboard. Tiles are added in the order this skill is called for a given dashboard_id.

CRITICAL ORDER OF OPERATIONS:

Create the dashboard using make_dashboard.
Add any dashboard-level filters using add_dashboard_filter.
Then, add elements (tiles) using this skill.

Required Parameters:

dashboard_id: The ID of the target dashboard, obtained from make_dashboard.
model_name, explore_name, fields: These query parameters are inherited from the query skill and are required to define the data for the tile.

Optional Parameters:

title: An optional title for the dashboard tile.
pivots, filters, sorts, limit, query_timezone: These query parameters are inherited from the query skill and can be used to customize the tile's query.
vis_config: A JSON object defining the visualization settings for this tile. The structure and options are the same as for the query_url skill's vis_config.

Connecting to Dashboard Filters: A dashboard element can be connected to one or more dashboard filters (created with add_dashboard_filter). To do this, specify the name of the dashboard filter and the field from the element's query that the filter should apply to. The format for specifying the field is view_name.field_name.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
dashboard_id	string	The id of the dashboard where this tile will exist	Yes
title	string	The title of the Dashboard Element	No	``
vis_config	object	The visualization config for the query	No	`map[]`
dashboard_filters	array	An array of dashboard filters like [{"dashboard_filter_name": "name", "field": "view_name.field_name"}, ...]	No

add_dashboard_filter

This skill adds a filter to a Looker dashboard.

CRITICAL ORDER OF OPERATIONS:

Create a dashboard using make_dashboard.
Add all desired filters using this skill (add_dashboard_filter).
Finally, add dashboard elements (tiles) using add_dashboard_element.

Parameters:

dashboard_id (required): The ID from make_dashboard.
name (required): A unique internal identifier for the filter. You will use this name later in add_dashboard_element to bind tiles to this filter.
title (required): The label displayed to users in the UI.
filter_type (required): One of date_filter, number_filter, string_filter, or field_filter.
default_value (optional): The initial value for the filter.

Field Filters (filter_type: field_filter): If creating a field filter, you must also provide:

model
explore
dimension The filter will inherit suggestions and type information from this LookML field.

Parameters

Name	Type	Description	Required	Default
dashboard_id	string	The id of the dashboard where this filter will exist	Yes
name	string	The name of the Dashboard Filter	Yes
title	string	The title of the Dashboard Filter	Yes
filter_type	string	The filter_type of the Dashboard Filter: date_filter, number_filter, string_filter, field_filter (default field_filter)	No	`field_filter`
default_value	string	The default_value of the Dashboard Filter (optional)	No
model	string	The model of a field type Dashboard Filter (required if type field)	No
explore	string	The explore of a field type Dashboard Filter (required if type field)	No
dimension	string	The dimension of a field type Dashboard Filter (required if type field)	No
allow_multiple_values	boolean	The Dashboard Filter should allow multiple values (default true)	No	`true`
required	boolean	The Dashboard Filter is required to run dashboard (default false)	No	`false`

generate_embed_url

This skill generates a signed, private embed URL for specific Looker content, allowing users to access it directly.

Parameters:

type (required): The type of content to embed. Common values include:
- dashboards
- looks
- explore
id (required): The unique identifier for the content.
- For dashboards and looks, use the numeric ID (e.g., "123").
- For explores, use the format "model_name/explore_name".

Parameters

Name	Type	Description	Required	Default
type	string	Type of Looker content to embed (ie. dashboards, looks, query-visualization)	No	``
id	string	The ID of the content to embed.	No	``

get_dashboards

This skill searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.

Search Parameters:

title (optional): Filter by dashboard title (supports wildcards).
folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
user_id (optional): Filter by the ID of the user who created the dashboard.
description (optional): Filter by description content (supports wildcards).
id (optional): Filter by specific dashboard ID.
limit (optional): Maximum number of results to return. Defaults to a system limit.
offset (optional): Starting point for pagination.

String Search Behavior:

Case-insensitive matching.
Supports SQL LIKE pattern match wildcards:
- %: Matches any sequence of zero or more characters. (e.g., "finan%" matches "financial", "finance")
- _: Matches any single character. (e.g., "s_les" matches "sales")
Special expressions for null checks:
- "IS NULL": Matches dashboards where the field is null.
- "NOT NULL": Excludes dashboards where the field is null.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the dashboard.	No	``
desc	string	The description of the dashboard.	No	``
limit	integer	The number of dashboards to fetch. Default 100	No	`100`
offset	integer	The number of dashboards to skip before fetching. Default 0	No	`0`

get_dimensions

This skill retrieves a list of dimensions defined within a specific Looker explore. Dimensions are non-aggregatable attributes or characteristics of your data (e.g., product name, order date, customer city) that can be used for grouping, filtering, or segmenting query results.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Output Details:

If a dimension includes a suggestions field, its contents are valid values that can be used directly as filters for that dimension.
If a suggest_explore and suggest_dimension are provided, you can query that specified explore and dimension to retrieve a list of valid filter values.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_explores

This skill retrieves a list of explores defined within a specific LookML model. Explores represent a curated view of your data, typically joining several tables together to allow for focused analysis on a particular subject area. The output provides details like the explore's name and label.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explores.	Yes

get_filters

This skill retrieves a list of "filter-only fields" defined within a specific Looker explore. These are special fields defined in LookML specifically to create user-facing filter controls that do not directly affect the GROUP BY clause of the SQL query. They are often used in conjunction with liquid templating to create dynamic queries.

Note: Regular dimensions and measures can also be used as filters in a query. This skill only returns fields explicitly defined as filter: in LookML.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_looks

This skill searches for saved Looks (pre-defined queries and visualizations) in a Looker instance. It returns a list of JSON objects, each representing a Look.

Search Parameters:

title (optional): Filter by Look title (supports wildcards).
folder_id (optional): Filter by the ID of the folder where the Look is saved.
user_id (optional): Filter by the ID of the user who created the Look.
description (optional): Filter by description content (supports wildcards).
id (optional): Filter by specific Look ID.
limit (optional): Maximum number of results to return. Defaults to a system limit.
offset (optional): Starting point for pagination.

String Search Behavior:

Case-insensitive matching.
Supports SQL LIKE pattern match wildcards:
- %: Matches any sequence of zero or more characters. (e.g., "dan%" matches "danger", "Danzig")
- _: Matches any single character. (e.g., "D_m%" matches "Damage", "dump")
Special expressions for null checks:
- "IS NULL": Matches Looks where the field is null.
- "NOT NULL": Excludes Looks where the field is null.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the look.	No	``
desc	string	The description of the look.	No	``
limit	integer	The number of looks to fetch. Default 100	No	`100`
offset	integer	The number of looks to skip before fetching. Default 0	No	`0`

get_measures

This skill retrieves a list of measures defined within a specific Looker explore. Measures are aggregatable metrics (e.g., total sales, average price, count of users) that are used for calculations and quantitative analysis in your queries.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Output Details:

If a measure includes a suggestions field, its contents are valid values that can be used directly as filters for that measure.
If a suggest_explore and suggest_dimension are provided, you can query that specified explore and dimension to retrieve a list of valid filter values.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_models

This skill retrieves a list of available LookML models in the Looker instance. LookML models define the data structure and relationships that users can query. The output includes details like the model's name and label, which are essential for subsequent calls to skills like get_explores or query.

This skill takes no parameters.

get_parameters

This skill retrieves a list of parameters defined within a specific Looker explore. LookML parameters are dynamic input fields that allow users to influence query behavior without directly modifying the underlying LookML. They are often used with liquid templating to create flexible dashboards and reports, enabling users to choose dimensions, measures, or other query components at runtime.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

make_dashboard

This skill creates a new, empty dashboard in Looker. Dashboards are stored in the user's personal folder, and the dashboard name must be unique. After creation, use add_dashboard_filter to add filters and add_dashboard_element to add content tiles.

Required Parameters:

title (required): A unique title for the new dashboard.
description (required): A brief description of the dashboard's purpose.

Output: A JSON object containing a link (url) to the newly created dashboard and its unique id. This dashboard_id is crucial for subsequent calls to add_dashboard_filter and add_dashboard_element.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the Dashboard	Yes
description	string	The description of the Dashboard	No	``
folder	string	The folder id where the Dashboard will be created. Leave blank to use the user's personal folder	No	``

make_look

This skill creates a new Look (saved query with visualization) in Looker. The Look will be saved in the user's personal folder, and its name must be unique.

Required Parameters:

title: A unique title for the new Look.
description: A brief description of the Look's purpose.
model_name: The name of the LookML model (from get_models).
explore_name: The name of the explore (from get_explores).
fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.

Optional Parameters:

pivots, filters, sorts, limit, query_timezone: These parameters are identical to those described for the query skill.
vis_config: A JSON object defining the visualization settings for the Look. The structure and options are the same as for the query_url skill's vis_config.

Output: A JSON object containing a link (url) to the newly created Look, along with its id and slug.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
title	string	The title of the Look	Yes
description	string	The description of the Look	No	``
folder	string	The folder id where the Look will be created. Leave blank to use the user's personal folder	No	``
vis_config	object	The visualization config for the query	No	`map[]`

query

This skill runs a query against a LookML model and returns the results in JSON format.

Required Parameters:

model_name: The name of the LookML model (from get_models).
explore_name: The name of the explore (from get_explores).
fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.

Optional Parameters:

pivots: A list of fields to pivot the results by. These fields must also be included in the fields list.
filters: A map of filter expressions, e.g., {"view.field": "value", "view.date": "7 days"}.
- Do not quote field names.
- Use not null instead of -NULL.
- If a value contains a comma, enclose it in single quotes (e.g., "'New York, NY'").
sorts: A list of fields to sort by, optionally including direction (e.g., ["view.field desc"]).
limit: Row limit (default 500). Use "-1" for unlimited.
query_timezone: specific timezone for the query (e.g. America/Los_Angeles).

Note: Use get_dimensions, get_measures, get_filters, and get_parameters to find valid fields.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No

query_sql

This skill generates the underlying SQL query that Looker would execute against the database for a given set of parameters. It is useful for understanding how Looker translates a request into SQL.

Parameters: All parameters for this skill are identical to those of the query skill. This includes model_name, explore_name, fields (required), and optional parameters like pivots, filters, sorts, limit, and query_timezone.

Output: The result of this skill is the raw SQL text.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No

query_url

This skill generates a shareable URL for a Looker query, allowing users to explore the query further within the Looker UI. It returns the generated URL, along with the query_id and slug.

Parameters: All query parameters (e.g., model_name, explore_name, fields, pivots, filters, sorts, limit, query_timezone) are the same as the query skill.

Additionally, it accepts an optional vis_config parameter:

vis_config (optional): A JSON object that controls the default visualization settings for the generated query.

vis_config Details: The vis_config object supports a wide range of properties for various chart types. Here are some notes on making visualizations.

Cartesian Charts (Area, Bar, Column, Line, Scatter)

These chart types share a large number of configuration options.

General

type: The type of visualization (looker_area, looker_bar, looker_column, looker_line, looker_scatter).
series_types: Override the chart type for individual series.
show_view_names: Display view names in labels and tooltips (true/false).
series_labels: Provide custom names for series.

Styling & Colors

colors: An array of color values to be used for the chart series.
series_colors: A mapping of series names to specific color values.
color_application: Advanced controls for color palette application (collection, palette, reverse, etc.).
font_size: Font size for labels (e.g., '12px').

Legend

hide_legend: Show or hide the chart legend (true/false).
legend_position: Placement of the legend ('center', 'left', 'right').

Axes

swap_axes: Swap the X and Y axes (true/false).
x_axis_scale: Scale of the x-axis ('auto', 'ordinal', 'linear', 'time').
x_axis_reversed, y_axis_reversed: Reverse the direction of an axis (true/false).
x_axis_gridlines, y_axis_gridlines: Display gridlines for an axis (true/false).
show_x_axis_label, show_y_axis_label: Show or hide the axis title (true/false).
show_x_axis_ticks, show_y_axis_ticks: Show or hide axis tick marks (true/false).
x_axis_label, y_axis_label: Set a custom title for an axis.
x_axis_datetime_label: A format string for datetime labels on the x-axis (e.g., '%Y-%m').
x_padding_left, x_padding_right: Adjust padding on the ends of the x-axis.
x_axis_label_rotation, x_axis_label_rotation_bar: Set rotation for x-axis labels.
x_axis_zoom, y_axis_zoom: Enable zooming on an axis (true/false).
y_axes: An array of configuration objects for multiple y-axes.

Data & Series

stacking: How to stack series ('' for none, 'normal', 'percent').
ordering: Order of series in a stack ('none', etc.).
limit_displayed_rows: Enable or disable limiting the number of rows displayed (true/false).
limit_displayed_rows_values: Configuration for the row limit (e.g., { "first_last": "first", "show_hide": "show", "num_rows": 10 }).
discontinuous_nulls: How to render null values in line charts (true/false).
point_style: Style for points on line and area charts ('none', 'circle', 'circle_outline').
series_point_styles: Override point styles for individual series.
interpolation: Line interpolation style ('linear', 'monotone', 'step', etc.).
show_value_labels: Display values on data points (true/false).
label_value_format: A format string for value labels.
show_totals_labels: Display total labels on stacked charts (true/false).
totals_color: Color for total labels.
show_silhouette: Display a "silhouette" of hidden series in stacked charts (true/false).
hidden_series: An array of series names to hide from the visualization.

Scatter/Bubble Specific

size_by_field: The field used to determine the size of bubbles.
color_by_field: The field used to determine the color of bubbles.
plot_size_by_field: Whether to display the size-by field in the legend.
cluster_points: Group nearby points into clusters (true/false).
quadrants_enabled: Display quadrants on the chart (true/false).
quadrant_properties: Configuration for quadrant labels and colors.
custom_quadrant_value_x, custom_quadrant_value_y: Set quadrant boundaries as a percentage.
custom_quadrant_point_x, custom_quadrant_point_y: Set quadrant boundaries to a specific value.

Miscellaneous

reference_lines: Configuration for displaying reference lines.
trend_lines: Configuration for displaying trend lines.
trellis: Configuration for creating trellis (small multiple) charts.
crossfilterEnabled, crossfilters: Configuration for cross-filtering interactions.

Boxplot

Inherits most of the Cartesian chart options.
type: Must be looker_boxplot.

Funnel

type: Must be looker_funnel.
orientation: How data is read ('automatic', 'dataInRows', 'dataInColumns').
percentType: How percentages are calculated ('percentOfMaxValue', 'percentOfPriorRow').
labelPosition, valuePosition, percentPosition: Placement of labels ('left', 'right', 'inline', 'hidden').
labelColor, labelColorEnabled: Set a custom color for labels.
labelOverlap: Allow labels to overlap (true/false).
barColors: An array of colors for the funnel steps.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.

Pie / Donut

Pie charts must have exactly one dimension and one numerical measure.
type: Must be looker_pie.
value_labels: Where to display values ('legend', 'labels').
label_type: The format of data labels ('labPer', 'labVal', 'lab', 'val', 'per').
start_angle, end_angle: The start and end angles of the pie chart.
inner_radius: The inner radius, used to create a donut chart.
series_colors, series_labels: Override colors and labels for specific slices.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.
advanced_vis_config: A string containing JSON for advanced Highcharts configuration.

Waterfall

Inherits most of the Cartesian chart options.
type: Must be looker_waterfall.
up_color: Color for positive (increasing) values.
down_color: Color for negative (decreasing) values.
total_color: Color for the total bar.

Word Cloud

type: Must be looker_wordcloud.
rotation: Enable random word rotation (true/false).
colors: An array of colors for the words.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.

These are some sample vis_config settings.

A bar chart - {{ "defaults_version": 1, "label_density": 25, "legend_position": "center", "limit_displayed_rows": false, "ordering": "none", "plot_size_by_field": false, "point_style": "none", "show_null_labels": false, "show_silhouette": false, "show_totals_labels": false, "show_value_labels": false, "show_view_names": false, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "stacking": "normal", "totals_color": "#808080", "trellis": "", "type": "looker_bar", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "x_axis_zoom": true, "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5, "y_axis_zoom": true }}

A column chart with an option advanced_vis_config - {{ "advanced_vis_config": "{ chart: { type: 'pie', spacingBottom: 50, spacingLeft: 50, spacingRight: 50, spacingTop: 50, }, legend: { enabled: false, }, plotOptions: { pie: { dataLabels: { enabled: true, format: '\u003cb\u003e{key}\u003c/b\u003e\u003cspan style="font-weight: normal"\u003e - {percentage:.2f}%\u003c/span\u003e', }, showInLegend: false, }, }, series: [], }", "colors": [ "grey" ], "defaults_version": 1, "hidden_fields": [], "label_density": 25, "legend_position": "center", "limit_displayed_rows": false, "note_display": "below", "note_state": "collapsed", "note_text": "Unsold inventory only", "ordering": "none", "plot_size_by_field": false, "point_style": "none", "series_colors": {}, "show_null_labels": false, "show_silhouette": false, "show_totals_labels": false, "show_value_labels": true, "show_view_names": false, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "stacking": "normal", "totals_color": "#808080", "trellis": "", "type": "looker_column", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "x_axis_zoom": true, "y_axes": [], "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5, "y_axis_zoom": true }}

A line chart - {{ "defaults_version": 1, "hidden_pivots": {}, "hidden_series": [], "interpolation": "linear", "label_density": 25, "legend_position": "center", "limit_displayed_rows": false, "plot_size_by_field": false, "point_style": "none", "series_types": {}, "show_null_points": true, "show_value_labels": false, "show_view_names": false, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "stacking": "", "trellis": "", "type": "looker_line", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5 }}

An area chart - {{ "defaults_version": 1, "interpolation": "linear", "label_density": 25, "legend_position": "center", "limit_displayed_rows": false, "plot_size_by_field": false, "point_style": "none", "series_types": {}, "show_null_points": true, "show_silhouette": false, "show_totals_labels": false, "show_value_labels": false, "show_view_names": false, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "stacking": "normal", "totals_color": "#808080", "trellis": "", "type": "looker_area", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "x_axis_zoom": true, "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5, "y_axis_zoom": true }}

A scatter plot - {{ "cluster_points": false, "custom_quadrant_point_x": 5, "custom_quadrant_point_y": 5, "custom_value_label_column": "", "custom_x_column": "", "custom_y_column": "", "defaults_version": 1, "hidden_fields": [], "hidden_pivots": {}, "hidden_points_if_no": [], "hidden_series": [], "interpolation": "linear", "label_density": 25, "legend_position": "center", "limit_displayed_rows": false, "limit_displayed_rows_values": { "first_last": "first", "num_rows": 0, "show_hide": "hide" }, "plot_size_by_field": false, "point_style": "circle", "quadrant_properties": { "0": { "color": "", "label": "Quadrant 1" }, "1": { "color": "", "label": "Quadrant 2" }, "2": { "color": "", "label": "Quadrant 3" }, "3": { "color": "", "label": "Quadrant 4" } }, "quadrants_enabled": false, "series_labels": {}, "series_types": {}, "show_null_points": false, "show_value_labels": false, "show_view_names": true, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "size_by_field": "roi", "stacking": "normal", "swap_axes": true, "trellis": "", "type": "looker_scatter", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "x_axis_zoom": true, "y_axes": [ { "label": "", "orientation": "bottom", "series": [ { "axisId": "Channel_0 - average_of_roi_first", "id": "Channel_0 - average_of_roi_first", "name": "Channel_0" }, { "axisId": "Channel_1 - average_of_roi_first", "id": "Channel_1 - average_of_roi_first", "name": "Channel_1" }, { "axisId": "Channel_2 - average_of_roi_first", "id": "Channel_2 - average_of_roi_first", "name": "Channel_2" }, { "axisId": "Channel_3 - average_of_roi_first", "id": "Channel_3 - average_of_roi_first", "name": "Channel_3" }, { "axisId": "Channel_4 - average_of_roi_first", "id": "Channel_4 - average_of_roi_first", "name": "Channel_4" } ], "showLabels": true, "showValues": true, "tickDensity": "custom", "tickDensityCustom": 100, "type": "linear", "unpinAxis": false } ], "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5, "y_axis_zoom": true }}

A single record visualization - {{ "defaults_version": 1, "show_view_names": false, "type": "looker_single_record" }}

A single value visualization - {{ "comparison_reverse_colors": false, "comparison_type": "value", "conditional_formatting_include_nulls": false, "conditional_formatting_include_totals": false, "custom_color": "#1A73E8", "custom_color_enabled": true, "defaults_version": 1, "enable_conditional_formatting": false, "series_types": {}, "show_comparison": false, "show_comparison_label": true, "show_single_value_title": true, "single_value_title": "Total Clicks", "type": "single_value" }}

A Pie chart - {{ "defaults_version": 1, "label_density": 25, "label_type": "labPer", "legend_position": "center", "limit_displayed_rows": false, "ordering": "none", "plot_size_by_field": false, "point_style": "none", "series_types": {}, "show_null_labels": false, "show_silhouette": false, "show_totals_labels": false, "show_value_labels": false, "show_view_names": false, "show_x_axis_label": true, "show_x_axis_ticks": true, "show_y_axis_labels": true, "show_y_axis_ticks": true, "stacking": "", "totals_color": "#808080", "trellis": "", "type": "looker_pie", "value_labels": "legend", "x_axis_gridlines": false, "x_axis_reversed": false, "x_axis_scale": "auto", "y_axis_combined": true, "y_axis_gridlines": true, "y_axis_reversed": false, "y_axis_scale_mode": "linear", "y_axis_tick_density": "default", "y_axis_tick_density_custom": 5 }}

The result is a JSON object with the id, slug, the url, and the long_url.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
vis_config	object	The visualization config for the query	No	`map[]`

run_dashboard

This skill executes the queries associated with each tile in a specified dashboard and returns the aggregated data in a JSON structure.

Parameters:

dashboard_id (required): The unique identifier of the dashboard to run, typically obtained from the get_dashboards skill.

Output: The data from all dashboard tiles is returned as a JSON object.

Parameters

Name	Type	Description	Required	Default
dashboard_id	string	The id of the dashboard to run.	Yes

run_look

This skill executes the query associated with a saved Look and returns the resulting data in a JSON structure.

Parameters:

look_id (required): The unique identifier of the Look to run, typically obtained from the get_looks skill.

Output: The query results are returned as a JSON object.

Parameters

Name	Type	Description	Required	Default
look_id	string	The id of the look to run.	Yes
limit	integer	The row limit. Default 500	No	`500`

name	looker
description	These skills are designed for data discovery and business intelligence.

Usage

All scripts can be executed using Node.js. Replace <param_name> and <param_value> with actual values.

Bash: node <skill_dir>/scripts/<script_name>.js '{"<param_name>": "<param_value>"}'

PowerShell: node <skill_dir>/scripts/<script_name>.js '{\"<param_name>\": \"<param_value>\"}'

Note: The scripts automatically load the environment variables from various .env files. Do not ask the user to set vars unless skill executions fails due to env var absence.

Scripts

add_dashboard_element

This skill creates a new tile (element) within an existing Looker dashboard. Tiles are added in the order this skill is called for a given dashboard_id.

CRITICAL ORDER OF OPERATIONS:

Create the dashboard using make_dashboard.
Add any dashboard-level filters using add_dashboard_filter.
Then, add elements (tiles) using this skill.

Required Parameters:

dashboard_id: The ID of the target dashboard, obtained from make_dashboard.
model_name, explore_name, fields: These query parameters are inherited from the query skill and are required to define the data for the tile.

Optional Parameters:

title: An optional title for the dashboard tile.
pivots, filters, sorts, limit, query_timezone: These query parameters are inherited from the query skill and can be used to customize the tile's query.
vis_config: A JSON object defining the visualization settings for this tile. The structure and options are the same as for the query_url skill's vis_config.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
dashboard_id	string	The id of the dashboard where this tile will exist	Yes
title	string	The title of the Dashboard Element	No	``
vis_config	object	The visualization config for the query	No	`map[]`
dashboard_filters	array	An array of dashboard filters like [{"dashboard_filter_name": "name", "field": "view_name.field_name"}, ...]	No

add_dashboard_filter

This skill adds a filter to a Looker dashboard.

CRITICAL ORDER OF OPERATIONS:

Create a dashboard using make_dashboard.
Add all desired filters using this skill (add_dashboard_filter).
Finally, add dashboard elements (tiles) using add_dashboard_element.

Parameters:

dashboard_id (required): The ID from make_dashboard.
name (required): A unique internal identifier for the filter. You will use this name later in add_dashboard_element to bind tiles to this filter.
title (required): The label displayed to users in the UI.
filter_type (required): One of date_filter, number_filter, string_filter, or field_filter.
default_value (optional): The initial value for the filter.

Field Filters (filter_type: field_filter): If creating a field filter, you must also provide:

model
explore
dimension The filter will inherit suggestions and type information from this LookML field.

Parameters

Name	Type	Description	Required	Default
dashboard_id	string	The id of the dashboard where this filter will exist	Yes
name	string	The name of the Dashboard Filter	Yes
title	string	The title of the Dashboard Filter	Yes
filter_type	string	The filter_type of the Dashboard Filter: date_filter, number_filter, string_filter, field_filter (default field_filter)	No	`field_filter`
default_value	string	The default_value of the Dashboard Filter (optional)	No
model	string	The model of a field type Dashboard Filter (required if type field)	No
explore	string	The explore of a field type Dashboard Filter (required if type field)	No
dimension	string	The dimension of a field type Dashboard Filter (required if type field)	No
allow_multiple_values	boolean	The Dashboard Filter should allow multiple values (default true)	No	`true`
required	boolean	The Dashboard Filter is required to run dashboard (default false)	No	`false`

generate_embed_url

This skill generates a signed, private embed URL for specific Looker content, allowing users to access it directly.

Parameters:

type (required): The type of content to embed. Common values include:
- dashboards
- looks
- explore
id (required): The unique identifier for the content.
- For dashboards and looks, use the numeric ID (e.g., "123").
- For explores, use the format "model_name/explore_name".

Parameters

Name	Type	Description	Required	Default
type	string	Type of Looker content to embed (ie. dashboards, looks, query-visualization)	No	``
id	string	The ID of the content to embed.	No	``

get_dashboards

This skill searches for saved dashboards in a Looker instance. It returns a list of JSON objects, each representing a dashboard.

Search Parameters:

title (optional): Filter by dashboard title (supports wildcards).
folder_id (optional): Filter by the ID of the folder where the dashboard is saved.
user_id (optional): Filter by the ID of the user who created the dashboard.
description (optional): Filter by description content (supports wildcards).
id (optional): Filter by specific dashboard ID.
limit (optional): Maximum number of results to return. Defaults to a system limit.
offset (optional): Starting point for pagination.

String Search Behavior:

Case-insensitive matching.
Supports SQL LIKE pattern match wildcards:
- %: Matches any sequence of zero or more characters. (e.g., "finan%" matches "financial", "finance")
- _: Matches any single character. (e.g., "s_les" matches "sales")
Special expressions for null checks:
- "IS NULL": Matches dashboards where the field is null.
- "NOT NULL": Excludes dashboards where the field is null.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the dashboard.	No	``
desc	string	The description of the dashboard.	No	``
limit	integer	The number of dashboards to fetch. Default 100	No	`100`
offset	integer	The number of dashboards to skip before fetching. Default 0	No	`0`

get_dimensions

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Output Details:

If a dimension includes a suggestions field, its contents are valid values that can be used directly as filters for that dimension.
If a suggest_explore and suggest_dimension are provided, you can query that specified explore and dimension to retrieve a list of valid filter values.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_explores

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explores.	Yes

get_filters

Note: Regular dimensions and measures can also be used as filters in a query. This skill only returns fields explicitly defined as filter: in LookML.

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_looks

This skill searches for saved Looks (pre-defined queries and visualizations) in a Looker instance. It returns a list of JSON objects, each representing a Look.

Search Parameters:

title (optional): Filter by Look title (supports wildcards).
folder_id (optional): Filter by the ID of the folder where the Look is saved.
user_id (optional): Filter by the ID of the user who created the Look.
description (optional): Filter by description content (supports wildcards).
id (optional): Filter by specific Look ID.
limit (optional): Maximum number of results to return. Defaults to a system limit.
offset (optional): Starting point for pagination.

String Search Behavior:

Case-insensitive matching.
Supports SQL LIKE pattern match wildcards:
- %: Matches any sequence of zero or more characters. (e.g., "dan%" matches "danger", "Danzig")
- _: Matches any single character. (e.g., "D_m%" matches "Damage", "dump")
Special expressions for null checks:
- "IS NULL": Matches Looks where the field is null.
- "NOT NULL": Excludes Looks where the field is null.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the look.	No	``
desc	string	The description of the look.	No	``
limit	integer	The number of looks to fetch. Default 100	No	`100`
offset	integer	The number of looks to skip before fetching. Default 0	No	`0`

get_measures

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Output Details:

If a measure includes a suggestions field, its contents are valid values that can be used directly as filters for that measure.
If a suggest_explore and suggest_dimension are provided, you can query that specified explore and dimension to retrieve a list of valid filter values.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

get_models

This skill takes no parameters.

get_parameters

Parameters:

model_name (required): The name of the LookML model, obtained from get_models.
explore_name (required): The name of the explore within the model, obtained from get_explores.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore containing the fields.	Yes

make_dashboard

Required Parameters:

title (required): A unique title for the new dashboard.
description (required): A brief description of the dashboard's purpose.

Parameters

Name	Type	Description	Required	Default
title	string	The title of the Dashboard	Yes
description	string	The description of the Dashboard	No	``
folder	string	The folder id where the Dashboard will be created. Leave blank to use the user's personal folder	No	``

make_look

This skill creates a new Look (saved query with visualization) in Looker. The Look will be saved in the user's personal folder, and its name must be unique.

Required Parameters:

title: A unique title for the new Look.
description: A brief description of the Look's purpose.
model_name: The name of the LookML model (from get_models).
explore_name: The name of the explore (from get_explores).
fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.

Optional Parameters:

pivots, filters, sorts, limit, query_timezone: These parameters are identical to those described for the query skill.
vis_config: A JSON object defining the visualization settings for the Look. The structure and options are the same as for the query_url skill's vis_config.

Output: A JSON object containing a link (url) to the newly created Look, along with its id and slug.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
title	string	The title of the Look	Yes
description	string	The description of the Look	No	``
folder	string	The folder id where the Look will be created. Leave blank to use the user's personal folder	No	``
vis_config	object	The visualization config for the query	No	`map[]`

query

This skill runs a query against a LookML model and returns the results in JSON format.

Required Parameters:

model_name: The name of the LookML model (from get_models).
explore_name: The name of the explore (from get_explores).
fields: A list of field names (dimensions, measures, filters, or parameters) to include in the query.

Optional Parameters:

pivots: A list of fields to pivot the results by. These fields must also be included in the fields list.
filters: A map of filter expressions, e.g., {"view.field": "value", "view.date": "7 days"}.
- Do not quote field names.
- Use not null instead of -NULL.
- If a value contains a comma, enclose it in single quotes (e.g., "'New York, NY'").
sorts: A list of fields to sort by, optionally including direction (e.g., ["view.field desc"]).
limit: Row limit (default 500). Use "-1" for unlimited.
query_timezone: specific timezone for the query (e.g. America/Los_Angeles).

Note: Use get_dimensions, get_measures, get_filters, and get_parameters to find valid fields.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No

query_sql

This skill generates the underlying SQL query that Looker would execute against the database for a given set of parameters. It is useful for understanding how Looker translates a request into SQL.

Output: The result of this skill is the raw SQL text.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No

query_url

This skill generates a shareable URL for a Looker query, allowing users to explore the query further within the Looker UI. It returns the generated URL, along with the query_id and slug.

Parameters: All query parameters (e.g., model_name, explore_name, fields, pivots, filters, sorts, limit, query_timezone) are the same as the query skill.

Additionally, it accepts an optional vis_config parameter:

vis_config (optional): A JSON object that controls the default visualization settings for the generated query.

vis_config Details: The vis_config object supports a wide range of properties for various chart types. Here are some notes on making visualizations.

Cartesian Charts (Area, Bar, Column, Line, Scatter)

These chart types share a large number of configuration options.

General

type: The type of visualization (looker_area, looker_bar, looker_column, looker_line, looker_scatter).
series_types: Override the chart type for individual series.
show_view_names: Display view names in labels and tooltips (true/false).
series_labels: Provide custom names for series.

Styling & Colors

colors: An array of color values to be used for the chart series.
series_colors: A mapping of series names to specific color values.
color_application: Advanced controls for color palette application (collection, palette, reverse, etc.).
font_size: Font size for labels (e.g., '12px').

Legend

hide_legend: Show or hide the chart legend (true/false).
legend_position: Placement of the legend ('center', 'left', 'right').

Axes

swap_axes: Swap the X and Y axes (true/false).
x_axis_scale: Scale of the x-axis ('auto', 'ordinal', 'linear', 'time').
x_axis_reversed, y_axis_reversed: Reverse the direction of an axis (true/false).
x_axis_gridlines, y_axis_gridlines: Display gridlines for an axis (true/false).
show_x_axis_label, show_y_axis_label: Show or hide the axis title (true/false).
show_x_axis_ticks, show_y_axis_ticks: Show or hide axis tick marks (true/false).
x_axis_label, y_axis_label: Set a custom title for an axis.
x_axis_datetime_label: A format string for datetime labels on the x-axis (e.g., '%Y-%m').
x_padding_left, x_padding_right: Adjust padding on the ends of the x-axis.
x_axis_label_rotation, x_axis_label_rotation_bar: Set rotation for x-axis labels.
x_axis_zoom, y_axis_zoom: Enable zooming on an axis (true/false).
y_axes: An array of configuration objects for multiple y-axes.

Data & Series

stacking: How to stack series ('' for none, 'normal', 'percent').
ordering: Order of series in a stack ('none', etc.).
limit_displayed_rows: Enable or disable limiting the number of rows displayed (true/false).
limit_displayed_rows_values: Configuration for the row limit (e.g., { "first_last": "first", "show_hide": "show", "num_rows": 10 }).
discontinuous_nulls: How to render null values in line charts (true/false).
point_style: Style for points on line and area charts ('none', 'circle', 'circle_outline').
series_point_styles: Override point styles for individual series.
interpolation: Line interpolation style ('linear', 'monotone', 'step', etc.).
show_value_labels: Display values on data points (true/false).
label_value_format: A format string for value labels.
show_totals_labels: Display total labels on stacked charts (true/false).
totals_color: Color for total labels.
show_silhouette: Display a "silhouette" of hidden series in stacked charts (true/false).
hidden_series: An array of series names to hide from the visualization.

Scatter/Bubble Specific

size_by_field: The field used to determine the size of bubbles.
color_by_field: The field used to determine the color of bubbles.
plot_size_by_field: Whether to display the size-by field in the legend.
cluster_points: Group nearby points into clusters (true/false).
quadrants_enabled: Display quadrants on the chart (true/false).
quadrant_properties: Configuration for quadrant labels and colors.
custom_quadrant_value_x, custom_quadrant_value_y: Set quadrant boundaries as a percentage.
custom_quadrant_point_x, custom_quadrant_point_y: Set quadrant boundaries to a specific value.

Miscellaneous

reference_lines: Configuration for displaying reference lines.
trend_lines: Configuration for displaying trend lines.
trellis: Configuration for creating trellis (small multiple) charts.
crossfilterEnabled, crossfilters: Configuration for cross-filtering interactions.

Boxplot

Inherits most of the Cartesian chart options.
type: Must be looker_boxplot.

Funnel

type: Must be looker_funnel.
orientation: How data is read ('automatic', 'dataInRows', 'dataInColumns').
percentType: How percentages are calculated ('percentOfMaxValue', 'percentOfPriorRow').
labelPosition, valuePosition, percentPosition: Placement of labels ('left', 'right', 'inline', 'hidden').
labelColor, labelColorEnabled: Set a custom color for labels.
labelOverlap: Allow labels to overlap (true/false).
barColors: An array of colors for the funnel steps.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.

Pie / Donut

Pie charts must have exactly one dimension and one numerical measure.
type: Must be looker_pie.
value_labels: Where to display values ('legend', 'labels').
label_type: The format of data labels ('labPer', 'labVal', 'lab', 'val', 'per').
start_angle, end_angle: The start and end angles of the pie chart.
inner_radius: The inner radius, used to create a donut chart.
series_colors, series_labels: Override colors and labels for specific slices.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.
advanced_vis_config: A string containing JSON for advanced Highcharts configuration.

Waterfall

Inherits most of the Cartesian chart options.
type: Must be looker_waterfall.
up_color: Color for positive (increasing) values.
down_color: Color for negative (decreasing) values.
total_color: Color for the total bar.

Word Cloud

type: Must be looker_wordcloud.
rotation: Enable random word rotation (true/false).
colors: An array of colors for the words.
color_application: Advanced color palette controls.
crossfilterEnabled, crossfilters: Configuration for cross-filtering.

These are some sample vis_config settings.

A single record visualization - {{ "defaults_version": 1, "show_view_names": false, "type": "looker_single_record" }}

The result is a JSON object with the id, slug, the url, and the long_url.

Parameters

Name	Type	Description	Required	Default
model	string	The model containing the explore.	Yes
explore	string	The explore to be queried.	Yes
fields	array	The fields to be retrieved.	Yes
filters	object	The filters for the query	No	`map[]`
pivots	array	The query pivots (must be included in fields as well).	No	`[]`
sorts	array	The sorts like "field.id desc 0".	No	`[]`
limit	integer	The row limit.	No	`500`
tz	string	The query timezone.	No
vis_config	object	The visualization config for the query	No	`map[]`

run_dashboard

This skill executes the queries associated with each tile in a specified dashboard and returns the aggregated data in a JSON structure.

Parameters:

dashboard_id (required): The unique identifier of the dashboard to run, typically obtained from the get_dashboards skill.

Output: The data from all dashboard tiles is returned as a JSON object.

Parameters

Name	Type	Description	Required	Default
dashboard_id	string	The id of the dashboard to run.	Yes

run_look

This skill executes the query associated with a saved Look and returns the resulting data in a JSON structure.

Parameters:

look_id (required): The unique identifier of the Look to run, typically obtained from the get_looks skill.

Output: The query results are returned as a JSON object.

Parameters

Name	Type	Description	Required	Default
look_id	string	The id of the look to run.	Yes
limit	integer	The row limit. Default 500	No	`500`

looker

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get_filters

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get_models

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Parameters

run_dashboard

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run_look

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Usage

Scripts

add_dashboard_element

Parameters

add_dashboard_filter

Parameters

generate_embed_url

Parameters

get_dashboards

Parameters

get_dimensions

Parameters

get_explores

Parameters

get_filters

Parameters

get_looks

Parameters

get_measures

Parameters

get_models

get_parameters

Parameters

make_dashboard

Parameters

make_look

Parameters

query

Parameters

query_sql

Parameters

query_url

Cartesian Charts (Area, Bar, Column, Line, Scatter)

Boxplot