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Search Datasets

search_datasets
Read-onlyIdempotent

Search Palm Beach County GIS open geospatial datasets (parcels, addresses, zoning & public works) 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 (Palm Beach County GIS).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  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 establish read-only, idempotent, open-world behavior. The description adds value by specifying the output fields (name, summary, record_count, owner/org, Feature Service url) and the open-data scope, which goes beyond the structured annotation data.

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 sentences long, front-loads the action and resource, then states the return value and next steps. No wasted words; every phrase adds meaningful information.

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?

For a search tool with optional parameters, no output schema, and annotations covering safety, the description is effectively complete. It explains what is searched, what is returned, and how to use the result, making it self-sufficient for an agent.

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?

All three parameters (query, limit, org_id) have descriptions in the input schema covering 100% of them. The description's mention of 'keyword' only paraphrases the query parameter without adding any new semantic detail. Baseline of 3 is appropriate given full schema coverage.

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 a specific verb ('Search') and resource ('Palm Beach County GIS open geospatial datasets'), names concrete dataset categories (parcels, addresses, zoning), and clarifies its role by pointing to query_layer/layer_info for further use of the returned URL. This clearly distinguishes it 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 gives clear context: it is for keyword discovery of GIS datasets. It also advises passing the returned Feature Service URL to query_layer/layer_info, which serves as a next-step guideline. However, it does not explicitly state when NOT to use this tool or mention alternatives beyond those two.

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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TDQS

B3.4/5.0
Disambiguation2/5

Multiple tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all answer data questions, while discover_tools and suggest_questions both serve discovery. The three ArcGIS tools are distinct but are drowned out by the unrelated Pipeworx and prediction-market tools, making it hard to pick the right one.

Naming Consistency3/5

Tool names are mostly snake_case but mix verb_noun (query_layer, search_datasets, remember), noun_noun (layer_info, entity_profile), and less conventional forms (search_within, generate_llms_txt). The naming is readable and not chaotic, but there is no single consistent pattern across the set.

Tool Count1/5

34 tools is excessive for a server named 'Arcgis Palmbeach'. Only 3 tools are GIS-related (search_datasets, query_layer, layer_info); the other 31 are unrelated Pipeworx data, prediction-market, and memory utilities. The count grossly mismatches the server's apparent purpose.

Completeness1/5

For the stated ArcGIS/Palm Beach County GIS purpose, the tool surface is severely incomplete: only search, query, and layer-schema lookup exist, with no data editing, feature operations, or map-service management. While the Pipeworx domain is heavily covered, that is not what the server name promises, so the surface is a poor fit.