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Arcgis Sanclemente

by io.github.pipeworx-io
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Search Datasets

search_datasets
Read-onlyIdempotent

Search City of San Clemente 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 San Clemente 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

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds context about the return fields (name, summary, record_count, owner/org, url) and the intended follow-up action, which is useful beyond the 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?

Two sentences efficiently convey purpose, domain, return data, and workflow. No wasted words.

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?

Given the tool's moderate complexity, the description is highly complete: it specifies the domain (GIS open datasets), the search action, the return fields, and the next step (pass URL to related tools). Combined with full parameter schema and annotations, no information gaps remain.

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 baseline is 3. The description adds minimal parameter-level detail beyond the schema, though it reinforces the 'query' parameter purpose ('by keyword') and hints at the URL's role. No significant extra semantics.

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 searches 'City of San Clemente GIS open geospatial datasets' by keyword and returns specific fields, including a URL for subsequent use. This specifies the verb (search), resource (datasets), and scope (GIS open data), distinguishing it from siblings like 'query_layer' and 'layer_info' that operate on individual layers.

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 to search by keyword and mentions passing the returned URL to 'query_layer' / 'layer_info', establishing a workflow. However, it does not explicitly state when not to use this tool or list alternatives beyond the implicit workflow, lacking explicit exclusions.

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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