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Glama

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. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
      +  {
      +    "limit": 50,
      +    "out_fields": "*",
      +    "url": "https://gis.durham.gov/arcgis/rest/services/OpenData/Parcels/FeatureServer/0",
      +    "where": "1=1"
      +  },
      +  {
      +    "limit": 100,
      +    "order_by": "INCIDENT_TYPE ASC",
      +    "out_fields": "OBJECTID,ADDRESS,INCIDENT_TYPE",
      +    "url": "https://gis.durham.gov/arcgis/rest/services/OpenData/PublicSafety/FeatureServer/1",
      +    "where": "YEAR >= 2023"
      +  }
      +]
  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 and destructiveHint=false, so safety is covered. The description adds behavioral context by stating it returns attribute rows and geometry, and mentions pagination via offset and limit. This goes beyond the annotations without contradicting them.

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, front-loaded with the core action and parameter list. Every sentence adds value, and there is no redundancy or filler.

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 six parameters and no output schema, the description covers the tool's purpose, key parameter behaviors, return type (attribute rows and geometry), and a practical sampling pattern. It could mention error handling or response structure, but it is sufficient 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 coverage is 100% with descriptions for all six parameters. The description adds little semantic value beyond the schema—it reiterates 'SQL-like where' and 'comma-separated out_fields' which are already in the schema. The sampling tip is useful but more about usage than parameter meaning.

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', providing a specific verb and resource. It distinguishes from sibling tools like search_datasets (which finds datasets) and layer_info (which likely describes metadata) by focusing on querying layer data.

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 provides workflow context by noting the URL comes from search_datasets, and includes explicit usage tips such as using where='1=1' with out_fields='*' to sample. While this gives clear context, it does not explicitly exclude when not to use the tool or name alternative tools for different scenarios.

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

A3.8/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are near-identical entry points, and the polymarket family plus bet_research blur together. The three ArcGIS tools are distinct, but they are drowned out by a large set of overlapping data-research and prediction-market tools.

Naming Consistency3/5

There are clear naming families (ask_pipeworx*, polymarket_*, subscribe/unsubscribe) but overall conventions are mixed: verb_noun, noun_phrase, and domain-prefix styles all appear together. Everything uses snake_case, so it is still readable, but the pattern is not predictable across the full set.

Tool Count2/5

34 tools is a heavy surface, and the vast majority have nothing to do with the server's apparent ArcGIS Durham purpose—only search_datasets, query_layer, and layer_info are relevant. The count feels like a general-purpose data platform bolted onto a small GIS server rather than a well-scoped tool set.

Completeness2/5

For the implied ArcGIS Durham domain, the surface is thin: discover, schema, and query cover basic read-only geospatial access but omit broader GIS capabilities. For the much larger Pipeworx-looking surface, the completeness is hard to assess because the tools span unrelated domains without a coherent ArcGIS story.