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Maps Elevation

maps_elevation
Read-onlyIdempotent

"Elevation at [coords] via Google" / "altitude / height above sea level" — elevation in meters for one or more lat/lng pairs via Google Maps Elevation API. Pipe-separated locations for batch queries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
_apiKeyYesGoogle Maps API key
locationsYesPipe-separated "lat,lng" pairs (e.g., "39.7391,-104.9847|36.4555,-116.8666")

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusNoStatus of the elevation request
resultsNoElevation results for each location

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, destructiveHint=false. The description adds context: it uses the Google Maps Elevation API, supports batch queries via pipe-separated locations, and returns elevation in meters. This adds meaningful behavioral information beyond what annotations provide, though no details on API limits or error handling.

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, each serving a purpose: first sentence states the core function and data type, second explains the input format. It is front-loaded with key terms and contains no fluff. Ideal conciseness for an agent tool.

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 complexity (2 parameters, simple return value), annotations (safe read), and presence of output schema, the description covers the essential: purpose, input format, and data source. No missing information for an agent to correctly invoke the tool.

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?

The input schema fully describes both parameters (100% coverage), but the description adds value by explaining the format: 'Pipe-separated "lat,lng" pairs' and mentioning batch queries. This helps the agent understand the exact syntax required for the 'locations' parameter, going beyond the schema's generic description.

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 returns elevation in meters for lat/lng pairs via Google Maps Elevation API, using terms like 'elevation at [coords]' and 'altitude / height above sea level'. It distinguishes itself from sibling tools like maps_directions, maps_geocode, etc., by specifying the unique API and data type.

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 usage for elevation queries (e.g., 'elevation in meters for one or more lat/lng pairs') but provides no explicit guidance on when to use this tool versus alternatives, nor does it mention when not to use it. The context from sibling names suggests differentiation, but the description itself lacks direct usage guidance.

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

The tool set mixes unrelated domains (maps, prediction markets, npm dependencies, memory storage) under one server named 'Google_maps'. While individual tool descriptions are clear, an agent cannot easily distinguish which tools belong to the maps domain and which are extraneous, causing confusion about the server's actual purpose.

Naming Consistency2/5

Tool names lack a consistent convention. Maps tools use 'maps_' prefix, but other tools have names like 'ask_pipeworx', 'bet_research', 'forget', etc., mixing prefixes, verb styles, and underscore usage. No unified naming pattern across the set.

Tool Count2/5

37 tools is excessive for a specialized maps server. Only 7 tools are map-related; the remaining 30 cover disparate domains (financial data, prediction markets, system utilities), making the server seem like a random collection rather than a focused integration.

Completeness2/5

For a maps server, common operations like static map generation, place photos, or timezone lookups are missing. The inclusion of many non-maps tools creates a 'kitchen sink' effect, undermining completeness for the stated purpose. The tool surface is severely incomplete if judged by the server name.