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652036

ArcGIS Pro MCP

by 652036

Create Field Group

arcgis_pro_create_field_group
Destructive

Create a conditional field group in an ArcGIS dataset and read it back to verify it, using schema-change safeguards, exact target confirmation, and a fixed phrase.

Instructions

创建条件值字段组并读回核验;需要方案变更双门、目标精确回显和固定确认短语。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsYes
restrictiveNo
confirmationYes
dataset_pathYes
expected_datasetYes
field_group_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare destructiveHint=true, readOnlyHint=false, and idempotentHint=false, so the safety profile is largely covered. The description adds valuable behavioral context beyond annotations: read-back verification, a double-gate for schema changes, exact target echo, and a fixed confirmation phrase requirement. It does not detail what specifically gets destroyed, but provides meaningful operational constraints.

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

Conciseness4/5

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

A single compact sentence that front-loads the action ('创建条件值字段组') and follows with key requirements. Every phrase earns its place, though the density leaves some concepts underexplained rather than wasted.

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

Completeness3/5

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

Given a destructive create operation with 6 parameters and an output schema, the description is minimal. It adds important confirmation and verification context, but omits parameter-level guidance and alternative-tool routing, so an agent would still need to inspect the schema closely to invoke it correctly.

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

Parameters2/5

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

Schema description coverage is 0% across 6 parameters, so the description must compensate but largely does not. It indirectly references expected_dataset (目标精确回显) and confirmation (固定确认短语), but leaves fields, restrictive, dataset_path, and field_group_name unexplained, adding little semantic value for most parameters.

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?

States a specific verb and resource: '创建条件值字段组' (create conditional value field group) plus read-back verification. This distinguishes it from sibling tools like list_field_groups and delete_field_group, though it does not explicitly name alternatives. The purpose is clear but lacks explicit sibling differentiation.

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

Usage Guidelines3/5

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

Mentions prerequisites—'需要方案变更双门、目标精确回显和固定确认短语'—which imply when this tool is applicable, but offers no explicit guidance on when to use it versus alternatives such as add_contingent_value or other field-group tools. Usage is implied rather than stated.

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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