Get elevation statistics (Min, Average, Max) for 3×3, 5×5 and 7×7 pixel windows centred on the coordinates. Requires Pro or Enterprise key.
| Name | Required | Description | Default |
|---|---|---|---|
| lat | Yes | Latitude in decimal degrees (WGS-84). | |
| lon | Yes | Longitude in decimal degrees (WGS-84). | |
| dataset_id | Yes | Dataset identifier. |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the license requirement ('Requires Pro or Enterprise key'), directly states the computed statistics (Min, Average, Max) and window sizes, and the verb 'Get' implies a non-destructive read operation. This adds meaningful behavioral context beyond the schema.
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?
The description is two sentences long, front-loaded with the core function, and contains no unnecessary words. It efficiently conveys the purpose and a key prerequisite.
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 the simple tool (3 well-schema'd params, output schema present), the description covers all essential aspects: what it computes, the window sizes, and the license requirement. No additional context is needed for an agent to invoke it correctly.
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?
The input schema has 100% coverage with descriptions for all three parameters (lat, lon, dataset_id). The description does not add any parameter-specific semantics beyond what the schema already provides, so the baseline score of 3 applies.
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?
The description clearly states the tool retrieves elevation statistics (Min, Average, Max) for specific window sizes (3×3, 5×5, 7×7), which is a specific verb+resource+scope. It distinguishes itself from sibling tools like LP_Get_Elevation (single point) and LP_Get_Slope_Stats (slope vs elevation stats).
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?
The description implies usage for statistical elevation queries but does not explicitly state when to use this tool over siblings, nor does it mention alternatives. The only explicit note is the license requirement ('Requires Pro or Enterprise key'), which is a prerequisite rather than usage guidance.
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.
Each tool targets a distinct combination of variable (elevation, slope, terrain) and output type (point, batch, stats, chart, 3D, map), making selection unambiguous. The batch vs single-point tools are clearly differentiated by their input and purpose.
Eight of nine tools follow the consistent LP_Get_<Variable>_<OutputType> pattern, making the set predictable. The lone list_datasets deviates from this convention, creating a minor inconsistency.
With 9 tools, the server covers a focused domain (elevation, slope, terrain) without unnecessary bloat. Each tool serves a distinct purpose, and the count is well within the ideal 3-15 range.
The tool set is missing a single-point or batch slope query (e.g., LP_Get_Slope) while elevation has both single and batch versions. This asymmetry means agents cannot directly retrieve slope at a coordinate without using statistical aggregates, a notable gap.