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Layer Info

layer_info
Read-onlyIdempotent

Get an ArcGIS Feature/Map Service layer's schema by url: fields (name + type), geometry type, total record count, and capabilities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFeature/Map Service layer url, e.g. ".../FeatureServer/0".

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: +[
      +  {
      +    "url": "https://services.arcgis.com/sharing/rest/content/items/.../FeatureServer/0"
      +  }
      +]
  2. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds value by specifying exactly what metadata is fetched (fields, geometry type, record count, capabilities), which goes beyond the annotation signals. No contradictions or unexpected side effects are disclosed, but the description is sufficiently transparent for the tool's simplicity.

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?

One concise sentence front-loads the action and resource, followed by a compact list of return items. Every word earns its place with no redundancy or padding.

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 one-parameter read-only tool with rich annotations and full schema coverage, the description is complete. It names all major categories of returned information, and no output schema exists, so the description's enumeration of fields, geometry type, record count, and capabilities fully covers the expected result.

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?

The input schema has 100% coverage for the single 'url' parameter, including a full example. The description mentions 'by url' but adds no additional meaning beyond what the schema already provides, so the baseline of 3 is appropriate as the schema carries the semantic load.

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 ('Get') and clearly identifies the resource ('ArcGIS Feature/Map Service layer's schema') plus the exact information returned (fields, geometry type, total record count, capabilities). This distinguishes it from siblings like query_layer, which presumably retrieves data rather than schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need schema metadata) but does not explicitly contrast it with query_layer or other data-retrieval siblings. No direct exclusions or alternative tool names are provided, so the guidance is implicit rather than explicit.

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

A3.5/5.0
Disambiguation2/5

Several tools have overlapping purposes, e.g., multiple 'ask' tools (ask_pipeworx, ask_pipeworx_grounded, deep_research) and multiple 'compare' tools (compare_entities, scan_competitor_ai_presence). Descriptions are verbose but often don't clearly distinguish when to use each, causing confusion.

Naming Consistency1/5

Naming is highly inconsistent: snake_case (ai_visibility_check), camelCase (polymarket_fill_risk), and arbitrary prefixes (scan_, generate_, etc.). No consistent verb_noun pattern; e.g., 'query_layer' vs 'search_datasets' vs 'layer_info' all involve data retrieval but use different patterns.

Tool Count2/5

33 tools is excessive for a server purportedly focused on ArcGIS Carlsbad. Many tools are unrelated (e.g., polymarket betting, npm package scanning). The core ArcGIS functionality could be covered by 3-5 tools, but the server is bloated with Pipeworx utilities.

Completeness3/5

The ArcGIS portion lacks update/delete capabilities and is limited to querying. The Pipeworx tools cover a broad range of data sources but introduce many dependencies and meta-tools, creating a cluttered surface with dead ends (e.g., tools requiring paid accounts without fallback).