Get terrain slope statistics (Min, Average, Max) in degrees for 3×3, 5×5 and 7×7 pixel windows. WGS-84 corrected. Requires Pro 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?
With no annotations provided, the description carries the transparency burden. It discloses output units (degrees), the three window sizes, WGS-84 correction, and the Pro key requirement. It does not explicitly state that the operation is read-only, but the read-oriented nature is implicit and no contradiction exists.
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 a single, front-loaded sentence that packs purpose, units, window sizes, coordinate correction, and licensing without wasted words. Every clause adds value.
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?
The tool is simple (3 parameters, all described in schema) and has an output schema, so return values are covered. The description provides all essential operational context: what is computed, units, scales, coordinate correction, and access requirement. It is complete for an agent to select and invoke 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?
Schema description coverage is 100%, so each parameter (lat, lon, dataset_id) already has meaningful descriptions. The tool description adds little new parameter-specific detail beyond confirming WGS-84, which the schema already includes. Baseline of 3 is appropriate.
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's function: obtaining terrain slope statistics with explicit metrics (Min, Average, Max) in degrees and window sizes (3×3, 5×5, 7×7). This distinguishes it from sibling tools like LP_Get_Elevation_Stats and LP_Get_Slope_Chart.
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 slope statistics retrieval, and the 'Requires Pro key' line provides a prerequisite. However, it does not explicitly state when to prefer this over alternatives or when not to use it, offering only implied context.
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.