elevation_polyline"Elevation profile along [route]" / "topographic profile of [path]" / "how hilly is this trail" — elevation samples along a polyline (sequence of lat/lng). Use for hiking elevation gain, cycling grade, trail planning.
| Name | Required | Description | Default |
|---|---|---|---|
| coordinates | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {
+ "coordinates": [
+ [
+ -105.2705,
+ 40.015
+ ],
+ [
+ -105.269,
+ 40.016
+ ],
+ [
+ -105.2675,
+ 40.017
+ ]
+ ]
+ }
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. Description adds behavioral context (returns elevation samples along polyline) but does not elaborate on output format or limitations. Adequate given annotation coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with example queries and use cases, front-loaded with actionable phrases. Efficient, but could be more precise about coordinate order.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given one parameter, no output schema, and annotations covering safety, the description is adequate for a simple read tool. However, it lacks coordinate order specification and output details, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has one required parameter (coordinates) with 0% description coverage. Description says 'sequence of lat/lng' but example shows [lng, lat] order. This ambiguity and missing formal definition means the description adds limited value and may mislead.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'elevation samples along a polyline' and provides example use cases like hiking elevation gain, cycling grade, trail planning. It implicitly distinguishes from sibling tools like 'elevation' (likely single point).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit example queries and use cases ('Use for hiking elevation gain, cycling grade, trail planning'). No explicit when-not-to-use, but context is clear and distinguishes from polyline vs. point.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools have distinct purposes, but there is overlap, e.g., ask_pipeworx vs ask_pipeworx_grounded vs deep_research all for data lookup, and multiple Polymarket tools. Descriptions are detailed enough to distinguish, but the set is confusing.
Naming is highly inconsistent: snake_case (ai_visibility_check), verb_noun (resolve_entity), underscores (ask_pipeworx), and domain-specific prefixes (polymarket_). No consistent pattern across tools.
With 38 tools spanning geospatial, data lookup, prediction markets, memory, feedback, etc., the count is too high for a coherent server. Many tools are one-off and unrelated to the server's name (Maptiler).
The tool set covers many areas but lacks obvious gaps for each domain (e.g., MapTiler only has 4 tools). The overall surface is a collection of unrelated features, not a cohesive domain, so completeness is poor for any single purpose.