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652036

ArcGIS Pro MCP

by 652036

Add Contingent Value

arcgis_pro_add_contingent_value
Destructive

Add and verify unique ANY, NULL, CODED_VALUE, or RANGE contingent values in a field group, with schema-change gates and exact target confirmation.

Instructions

添加 ANY/NULL/CODED_VALUE/RANGE 条件值并核验唯一新增项;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
valuesYes
retiredNo
subtypeNo
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 destructive=true, idempotent=false, openWorld=false. The description adds genuinely useful behavior beyond that: verification that only a unique new item is created, a dual-gate scheme change requirement, exact target echo, and a fixed confirmation phrase. These are meaningful operational constraints not present in the annotations.

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 dense sentence with the action front-loaded and the constraints trailing; no filler. Slightly compressed for a tool with this many preconditions, but efficient.

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?

Output schema exists so return values need not be described, and behavior gates are covered, but with 7 parameters at 0% schema coverage critical input semantics remain undocumented. Adequate but with a clear gap for a destructive mutation.

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% and the description does not compensate: dataset_path, field_group_name, expected_dataset, confirmation, retired, and subtype are never explained. Only the value kinds are hinted at, leaving six of seven parameters semantically opaque.

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 (添加) plus resource (contingent values) and the value kinds it handles (ANY/NULL/CODED_VALUE/RANGE), which clearly separates it from list/remove/export/import siblings. Clear purpose, though it does not name an alternative sibling the way a 5 would.

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?

Implies usage through prerequisites (double-gate for scheme change, exact target echo, fixed confirmation phrase) but never states when to pick this over siblings or when not to use it. Usage is inferable rather than explicit.

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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