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Arcgis Sacramento

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://gis.data.sac.ca.us/arcgis/rest/services/OpenData/Parcels/FeatureServer/0",
+    "where": "1=1"
+  },
+  {
+    "limit": 100,
+    "out_fields": "PARCEL_ID,ZONING_CODE,ACRES",
+    "url": "https://gis.data.sac.ca.us/arcgis/rest/services/OpenData/Zoning/FeatureServer/0",
+    "where": "ZONING_CODE = 'R1'"
+  }
+]
  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 indicate read-only, idempotent, non-destructive behavior. The description adds that the tool returns 'attribute rows (and geometry)', which is behavioral context beyond annotations. However, it doesn't disclose pagination behavior or any limits beyond the schema's max 2000.

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 extremely concise: two sentences that first state the core function and parameters, then provide a practical usage tip. No redundant information, and the key verb ('Query') appears first, making it front-loaded and efficient.

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 tool's complexity (6 params, no output schema), the description covers essential context: the type of service, key parameters, and sample usage. It also links to the sibling tool 'search_datasets'. It could be improved by clarifying geometry format or pagination details, but overall it is sufficiently complete.

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%, so the description's mention of parameters ('SQL-like where', 'comma-separated out_fields', etc.) adds little beyond what the schema already provides. It does offer a high-level conceptual grouping, but the schema's own descriptions and examples are sufficiently clear.

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 action ('Query'), the resource ('ArcGIS Feature Service / Map Service layer'), and specifies usage context ('from search_datasets'). It also explicitly lists the parameters and provides an example usage, making the purpose unambiguous and distinct from sibling tools.

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 advises to use this tool after search_datasets, and gives a concrete example (where='1=1', out_fields='*') for sampling. It implies that the tool is for querying specific layers but doesn't explicitly state when not to use it or name alternatives, though the sibling tool 'layer_info' could be an alternative for metadata.

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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