arcpro-mcp

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Describe Data

describe_data

Read-only

Retrieve dataset properties such as data type, shape type, feature count, extent, and coordinate system to validate inputs before geoprocessing.

Instructions

Describe a dataset: data type, geometry/shape type, feature count, extent, and coordinate system (name, WKID, geographic vs projected, linear unit). Always check this before any distance- or area-based geoprocessing.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>"
    },
    "name": "describe_data"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Jun 14, 2026

TDQS

A4.1/5.0

Behavior4/5

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

The description reveals the tool returns detailed metadata about a dataset, which goes beyond the readOnlyHint annotation by specifying the exact information obtained. No side effects or authorization needs are mentioned, but for a read-only metadata tool this is sufficient.

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 two sentences: the first concisely lists the output properties, and the second provides a crucial usage hint. Every sentence adds value with no redundancy or verbosity.

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

Completeness4/5

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

Given the tool has only one parameter and an output schema (handling return values), the description adequately covers purpose, output, and usage context. It is sufficient for an agent to use the tool correctly, though parameter semantics could be improved.

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?

The single parameter 'path' has no description in the schema (0% coverage), and the tool description does not explain what 'path' refers to (e.g., file path, layer name, dataset identifier). The description fails to add meaning beyond the schema, forcing the agent to infer the required format.

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

Purpose5/5

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

The description clearly states the tool describes a dataset and enumerates the specific metadata returned (data type, geometry type, feature count, extent, coordinate system). It is a specific verb-resource pair that distinguishes itself from sibling tools like get_project_info or list_fields.

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

Usage Guidelines4/5

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

The description explicitly advises using this tool before any distance- or area-based geoprocessing, providing clear context for when to invoke it. It does not mention when not to use it or list alternative tools, but the guidance is strong and specific.

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