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Arcgis Cranston

by io.github.pipeworx-io
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Query Layer

query_layer
Read-onlyIdempotent

Query an ArcGIS Feature Service / Map Service layer by its url (from search_datasets). SQL-like where, comma-separated out_fields, order_by, limit, offset. Returns attribute rows (and geometry). Use where="1=1" + out_fields="*" to sample.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFeature/Map Service layer url ending in /FeatureServer/<n> or /MapServer/<n>.
limitNoMax features (1-2000, default 50).
whereNoSQL where clause, e.g. "STATE = 'CA' AND YEAR >= 2020". Default "1=1".
offsetNoPagination offset.
order_byNoe.g. "POP DESC".
out_fieldsNoComma-separated field names, or "*" for all (default).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "limit": 50,
+    "out_fields": "*",
+    "url": "https://services.arcgis.com/example/rest/services/Parcels/FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "order_by": "NAME ASC",
+    "out_fields": "OBJECTID,NAME,ADDRESS",
+    "url": "https://services.arcgis.com/example/rest/services/CityServices/FeatureServer/2",
+    "where": "SERVICE_TYPE = 'Police'"
+  }
+]
  2. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the agent knows this is a safe read operation. The description adds that it returns 'attribute rows (and geometry)' and suggests a sampling pattern, but does not discuss pagination limits, performance, or error behavior, which would be extra value beyond annotations. With annotations covering the safety profile, a 3 is appropriate.

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 three sentences, front-loaded with the core purpose. Each sentence adds unique value: purpose, parameter list, and a usage tip. There is no wasted or redundant language.

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?

With no output schema, the description partially compensates by stating return content ('attribute rows and geometry'). The annotations provide safety context, and the schema fully documents parameters. It could be improved by mentioning the default limit (50) or max limit, but for a query tool with strong structured metadata, this is 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?

Schema coverage is 100%, with each parameter described in the schema. The description mentions 'SQL-like `where`, comma-separated `out_fields`, `order_by`, `limit`, `offset`', which adds a little context about format, but the schema already provides detailed descriptions. The baseline of 3 applies because the schema does the heavy lifting.

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 verb 'Query' and resource 'ArcGIS Feature Service / Map Service layer', and specifies the URL source 'from search_datasets'. It distinguishes from siblings like layer_info (metadata) and search_datasets (discovery) by focusing on retrieving attribute rows and geometry.

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 by indicating the prerequisite workflow ('from search_datasets') and includes a practical sampling tip ('Use where="1=1" + out_fields="*"'). However, it does not explicitly mention when not to use this tool or name alternative tools for metadata discovery, only implying them.

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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