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tharlestsa

OpenLandMap MCP Server

by tharlestsa

get_vegetation_collections

Retrieve vegetation data collections including EVI, FAPAR, forest cover, potential vegetation, and plant functional types from the OpenLandMap STAC catalog for geospatial analysis.

Instructions

List all vegetation-related collections.

Returns collections about EVI, FAPAR, forest cover, potential vegetation, and plant functional types.

Returns: List of CollectionSummary dicts for vegetation collections.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the return type ('List of CollectionSummary dicts') and examples of collection types, but lacks details on permissions, rate limits, pagination, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose in the first sentence, followed by additional details on return content and format. It is efficient with minimal waste, though the 'Returns:' section could be integrated more smoothly. Overall, it is appropriately sized and structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (0 parameters, output schema exists), the description is adequate but has gaps. It covers the purpose and return examples, but lacks behavioral context (e.g., how it differs from siblings, any limitations). With an output schema, it need not explain return values in detail, but more guidance on usage would improve completeness.

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 has 0 parameters with 100% coverage, so no parameter information is needed. The description does not add parameter semantics, but this is acceptable given the schema's completeness. A baseline of 4 is appropriate for tools with no parameters, as there is nothing to compensate for.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'List all vegetation-related collections.' It specifies the verb ('List') and resource ('vegetation-related collections'), and provides examples of collection types (EVI, FAPAR, etc.). However, it does not explicitly differentiate from sibling tools like 'get_land_cover_collections' or 'get_soil_collections', which likely serve similar but distinct purposes, preventing a score of 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention sibling tools such as 'list_collections' (which might list all collections) or 'get_land_cover_collections' (which might focus on a subset), nor does it specify prerequisites or exclusions. Usage is implied by the purpose but not explicitly stated.

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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