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Arcgis Flagstaff

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/flagstaff/rest/services/Parcels/FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "order_by": "PARCEL_ID ASC",
+    "out_fields": "PARCEL_ID,ZONE_TYPE,OWNER",
+    "url": "https://services.arcgis.com/flagstaff/rest/services/Zoning/FeatureServer/0",
+    "where": "ZONE_TYPE = 'Residential'"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that the tool 'Returns attribute rows (and geometry)', which is useful behavioral context. It also clarifies the query style as 'SQL-like', without contradicting 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 a single sentence, front-loaded with the core action and source. It efficiently mentions all key parameters and gives a usage tip without 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?

The description covers the essential behavior (querying an ArcGIS layer), return type (attribute rows and geometry), and prerequisite (url from search_datasets). While there is no output schema, the description and annotations provide sufficient context for an agent to select and invoke the tool.

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 description coverage is 100%, with each parameter already documented. The description merely lists parameter names and gives a usage example, adding no new semantics beyond the schema. Baseline 3 is appropriate.

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 'Query an ArcGIS Feature Service / Map Service layer by its url', with a specific verb and resource. It also mentions the URL source 'from search_datasets', which distinguishes it from sibling tools like search_datasets or layer_info.

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 implies when to use the tool: after obtaining a URL from search_datasets. It also provides a practical sampling tip ('Use where="1=1" + out_fields="*" to sample'). It doesn't explicitly list exclusions but gives clear context for use.

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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