list_datasets
List all available elevation datasets on the Geospatial System server.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
List all available elevation datasets on the Geospatial System server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. The verb 'List' clearly indicates a read-only operation with no side effects. It doesn't provide additional details like authentication or pagination, but for a simple list operation, this is adequately transparent.
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 sentence that immediately states the action and resource. There is no redundant information, and every word 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?
Given the tool's simplicity (no parameters, output schema present), the description fully covers its purpose and scope. Sibling tools make the use case evident, and no additional details are needed for correct invocation.
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 tool has zero parameters, so the baseline is 4. No parameter documentation is needed, and the description's focus on the listing behavior is sufficient.
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 uses the specific verb 'List' with a clear resource ('all available elevation datasets') and context ('on the Geospatial System server'). It clearly distinguishes from sibling tools that retrieve specific elevation data, making the tool's purpose unambiguous.
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 use for discovering available datasets before selecting a specific data retrieval tool. It doesn't explicitly state when not to use it or name an alternative, but the context of sibling tools focused on retrieval makes the usage context clear.
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.