gisgp

query_statistics

Server-side aggregate stats on a numeric field of a FeatureServer layer.

No records fetched — AGOL computes sum/avg/min/max/count (also stddev/var).
Optional WHERE filter and group_by field. Returns JSON: {field, results:[...]}.
Cheap way to answer "what's the average/total of field X" without an export.

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": {
      "service_url": "<service_url>",
      "field": "<field>"
    },
    "name": "query_statistics"
  }
}

Input Schema

Name	Required	Default
`field`	Yes
`stats`	No	sum,avg,min,max,count
`token`	No
`where`	No	1=1
`group_by`	No
`service_url`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedJul 11, 2026

TDQS

A4.2/5.0

Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses key behaviors: no records fetched, AGOL computes stats, returns JSON, and describes optional filters. Could mention error handling or authentication but is fairly complete.

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 four sentences, each providing essential information: purpose, performance, options, and return value. No fluff or redundancy.

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 presence of an output schema and the tool's moderate complexity (6 params, 2 required), the description covers the core functionality and use case. Minor gaps remain (e.g., stats parameter details) but overall sufficient.

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?

With 0% schema description coverage, the description adds useful context (e.g., optional WHERE and group_by, return format) but does not fully explain each parameter, like the 'stats' parameter 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 computes server-side aggregate statistics on a numeric field of a FeatureServer layer, distinguishing it from similar tools like query_features by emphasizing no records are fetched and it's a cheap way to get summary values.

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 provides clear context on when to use (e.g., for aggregate stats without fetching records) but does not explicitly state when not to use or name alternative tools.

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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