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tharlestsa

OpenLandMap MCP Server

by tharlestsa

get_all_data_assets

Retrieve Cloud-Optimized GeoTIFF download URLs for raster data layers from OpenLandMap collections by filtering assets with role 'data'.

Instructions

Get only data assets (excluding thumbnails, styles).

Filters assets by role='data', returning only actual raster data layers (Cloud-Optimized GeoTIFFs). Useful when you need download URLs.

Args: collection_id: Collection identifier. item_id: Item identifier.

Returns: List of AssetInfo dicts with role 'data'.

Example: get_all_data_assets("organic.carbon_usda.6a1c", "organic.carbon_usda.6a1c_20180101_20181231")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_idYes
item_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it filters assets by role='data', excludes thumbnails and styles, and returns download URLs. However, it lacks details on permissions, rate limits, error handling, or pagination, which are important for a tool that accesses data assets.

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

Conciseness5/5

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

The description is well-structured and front-loaded with the core purpose, followed by details on filters, usage, parameters, returns, and an example. Every sentence adds value without redundancy, making it efficient and easy to scan.

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

Completeness4/5

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

Given the tool's complexity (filtering data assets), lack of annotations, and presence of an output schema (which handles return values), the description is mostly complete. It covers purpose, filters, usage, parameters, and an example. However, it could improve by addressing behavioral aspects like error cases or authentication needs, which are not covered by the output schema.

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?

Schema description coverage is 0%, so the description must compensate. It adds meaningful semantics by explaining that 'collection_id' and 'item_id' are identifiers for filtering assets, and the example provides concrete values. This clarifies parameter usage beyond the bare schema, though it could specify format constraints or relationships between parameters.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('Get', 'Filters', 'returning') and resources ('data assets', 'raster data layers', 'Cloud-Optimized GeoTIFFs'). It explicitly distinguishes this tool from siblings by specifying it excludes thumbnails and styles, unlike tools like 'get_visualization_assets' or 'list_assets_for_item' which might include all asset types.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool ('Useful when you need download URLs') and implicitly distinguishes it from alternatives by specifying it filters by role='data' and excludes other asset types. However, it does not explicitly name when-not-to-use cases or mention specific sibling tools as alternatives, such as 'get_visualization_assets' for non-data assets.

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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