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Arcgis Asheville

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

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already state readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds value by disclosing the return format ('attribute rows and geometry') and the sampling behavior, which goes beyond the structured annotations.

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 tight sentences. It front-loads the core action, lists key parameters compactly, and closes with a useful tip. Every word earns its place, and it is perfectly sized for the tool's complexity.

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

Completeness5/5

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

Even without an output schema, the description covers the tool's purpose, parameter semantics, return type (rows + geometry), and provides a usage example. It also names the prerequisite (search_datasets), making it sufficiently complete for an agent to select and invoke the tool correctly.

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?

The schema covers 100% of parameters, so the baseline is 3. The description adds semantic value by explaining 'SQL-like where' and providing a sampling usage example, which gives practical meaning beyond the raw schema 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 'Query an ArcGIS Feature Service / Map Service layer by its url', combining a specific verb ('Query') with a precise resource (ArcGIS layer). It also lists key parameters and mentions the url comes from search_datasets, which distinguishes it from sibling tools like layer_info or search_within.

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 gives clear context: the url should come from search_datasets, and it provides a practical tip ('Use where="1=1" + out_fields="*" to sample'). However, it does not explicitly mention alternatives or when not to use this tool, such as when metadata is needed (layer_info).

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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