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set_layer_labeling

Turn layer labels on or off and set the label expression, font, halo, and SQL filter in an ArcGIS Pro map.

Instructions

Turn labels on or off and set the expression, font and halo.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
boldNoBold text.
whereNoOnly label features matching this SQL clause.
italicNoItalic text.
enabledNoShow labels.
map_nameNoMap to act on; defaults to the active map.
font_sizeNoFont size in points.
halo_sizeNoHalo size in points.
expressionNoLabel expression, Arcade by default, e.g. "$feature.NAME".
font_colorNoFont colour as [r, g, b].
layer_nameYesLayer or table name as shown by get_layers, or a full dataset path.
font_familyNoFont name, e.g. "Tahoma".
expression_engineNoArcade, Python or VBScript.Arcade

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.1.1

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It does not disclose side effects, permissions, default behavior, whether existing label settings are overwritten, or what the required layer_name parameter does. For a 12-parameter mutation tool, this is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no redundant or wasted text. It is appropriately sized for a concise overview, though it is terse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 12 parameters, no annotations, and operates on layer labeling, the description is too sparse. While an output schema exists, the description still omits required input context, defaults, interaction with map_name, and behavioral details needed to invoke the tool confidently.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all 12 parameters thoroughly. The description mentions expression, font, and halo, which maps to some parameters, but adds no syntax, constraints, or meaning beyond what the schema provides. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action on a specific resource: turning labels on/off and setting label properties such as expression, font, and halo. It is clear what the tool does, but it does not explicitly differentiate itself from related siblings like set_layer_renderer or set_layer_visibility.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no when-to-use or when-not-to-use guidance, no prerequisites, and no mention of alternatives. It simply states the capability, leaving the agent to infer usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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