arcgis_pro_list_contingent_valuesRead a dataset's contingent values, filtered by exact field group and subtype code, to inspect valid coded values without altering the schema.
读取条件值清单，可按精确字段组和 subtype code 筛选，不修改方案。
| Name | Required | Description | Default |
|---|---|---|---|
| dataset_path | Yes | ||
| subtype_code | No | ||
| field_group_name | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v2.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered structurally. The description reinforces this with '不修改方案' (does not modify the schema), but adds no further behavioral context like output shape or empty-result behavior – acceptable given annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single compact sentence that front-loads the action, resources, filters, and non-mutation guarantee. No redundant phrasing and nothing extraneous.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
An output schema exists, so return-value explanations are not needed. However, with 0% schema description coverage the definition leaves parameter semantics undocumented and provides no usage routing among dozens of siblings, making it only minimally complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the three parameters have documented semantics in the schema. The description only names the filtering intent (field group, subtype code) without explaining format, expected values, or how dataset_path should be supplied, so it fails to compensate for the coverage gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb (读取/list) and resource (条件值/contingent values) and clearly names its two filterable dimensions (精确字段组和 subtype code). It also distinguishes itself from mutation siblings like add_contingent_value/remove_contingent_value by stating it does not modify the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (filtering by field group and subtype) but does not explicitly state when to prefer it over siblings such as list_field_groups or export_contingent_values. No when-not or prerequisite guidance is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.