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tharlestsa

OpenLandMap MCP Server

by tharlestsa

get_item_detail

Retrieve comprehensive metadata, assets, and spatial-temporal details for specific geospatial data items from OpenLandMap's global environmental datasets.

Instructions

Get full details for a specific STAC item including all assets.

Returns complete metadata, bounding box, geometry, temporal range, and all available assets with resolved URLs, MIME types, roles, and file sizes.

Args: collection_id: Collection identifier. item_id: Item identifier within the collection.

Returns: ItemDetail dict with geometry, properties, and assets list.

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
collection_idYes
item_idYes
Behavior2/5

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

With no annotations provided, the description carries the full burden. It describes the return content well but lacks critical behavioral details such as error handling, performance expectations, authentication requirements, or rate limits for a data retrieval tool.

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 returns, args, and an example. Every sentence adds value with no redundancy, making it efficient and easy to parse.

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?

For a tool with 2 parameters, no annotations, and no output schema, the description adequately covers purpose and parameters but lacks behavioral context (e.g., error cases, performance). It's minimally viable but leaves gaps in operational transparency.

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%, but the description compensates by clearly defining both parameters ('collection_id' and 'item_id') in the Args section and providing an example with realistic values, adding meaningful context beyond the bare schema.

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 specific action ('Get full details') and resource ('a specific STAC item including all assets'), distinguishing it from siblings like 'get_stac_item_as_geojson' or 'list_assets_for_item' by emphasizing comprehensive metadata retrieval.

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

Usage Guidelines3/5

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

Usage is implied through the description of what it returns (full details vs. partial), but there's no explicit guidance on when to use this tool over alternatives like 'get_stac_item_as_geojson' or 'list_assets_for_item'. The example helps illustrate typical use cases.

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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