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Arcgis Seattle

by io.github.pipeworx-io
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Search Datasets

search_datasets
Read-onlyIdempotent

Search City of Seattle GIS open geospatial datasets (parcels, zoning, public works & city services) by keyword. Returns each dataset's name, summary, record_count, owner/org, and its Feature Service url — pass that url to query_layer / layer_info.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax datasets (1-50, default 20).
queryNoKeyword(s), e.g. "parcels", "crime", "flood zones".
org_idNoOptional ArcGIS orgId to override the default (City of Seattle GIS).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "parcels"
+  },
+  {
+    "limit": 10,
+    "query": "zoning flood"
+  }
+]
  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 readOnlyHint and idempotentHint; description adds specific output fields and data source (City of Seattle GIS), confirming safe read behavior without contradiction.

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 tight sentences: first states purpose and scope, second details return fields and actionable guidance. No extraneous words, front-loaded with key information.

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 3 well-documented parameters, no output schema, and comprehensive annotations, the description sufficiently covers what the tool does, returns, and how to use the output. Missing details like pagination or field types are minor given schema examples.

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% with clear parameter descriptions. The description adds context about default org and suggests downstream tool usage, which aids agent understanding beyond schema alone.

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 uses specific verb 'search' and resource 'City of Seattle GIS open geospatial datasets', lists return fields, and distinguishes from sibling tools 'query_layer' and 'layer_info' by mentioning passing the url to them.

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 downstream usage guidance (pass url to query_layer/layer_info) and implies default org, but does not explicitly state when not to use or contrast with other search tool siblings like 'search_within' or 'deep_research'.

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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