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Arcgis Phoenix

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

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.arcgisonline.com/arcgis/rest/services/Phoenix/FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "order_by": "ADDRESS ASC",
+    "out_fields": "PARCEL_ID,ZONING,ADDRESS",
+    "url": "https://services.arcgisonline.com/arcgis/rest/services/Phoenix/FeatureServer/2",
+    "where": "ZONING = 'R1'"
+  }
+]
  2. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds value by mentioning return of attribute rows and geometry, and provides a sampling tip. It does not cover pagination limits or error handling, but the annotations lower the burden.

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?

Two sentences, front-loaded with the core action and key parameters, and includes a concise usage tip. No wasted words; every phrase earns its place.

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?

For a query tool with 6 parameters and no output schema, the description covers the primary use case, parameter summary, and return type. It lacks explicit error handling or rate limit info, but the sampling tip and provenance hint (from search_datasets) make it sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description supplements with SQL-like syntax examples and a sampling pattern ('where=1=1' + 'out_fields=*'), adding practical usage context beyond the schema's parameter descriptions.

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 queries an ArcGIS Feature/Map Service layer by URL, specifies the SQL-like parameters, and notes it returns attribute rows and geometry. This distinguishes it from siblings like layer_info (metadata) and search_within (geospatial search).

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 indicates it works with URLs from search_datasets and provides a sampling pattern ('where=1=1' + 'out_fields=*'), giving clear context. However, it does not explicitly state when to avoid this tool versus alternatives like layer_info or search_within.

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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