OpenLandMap MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what the tool does (comparison) and the output format ('CollectionComparison with one entry per collection'), but lacks details on permissions, rate limits, or error handling. It adds some context like the input range ('2-10') but could be more comprehensive for a tool with no annotation support.

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 well-structured and front-loaded with the core purpose, followed by usage context, args, returns, and an example. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 moderate complexity (one parameter but with specific constraints), no annotations, and no output schema, the description does a good job of covering purpose, usage, parameters, and output. It could improve by detailing the structure of 'CollectionComparison' or error cases, but it's largely complete for effective use.

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 description adds significant meaning beyond the input schema, which has 0% description coverage. It explains that 'collection_ids' is a list of IDs to compare, specifies the allowed range ('2-10'), and provides an example with actual IDs. This compensates well for the schema's lack of descriptions, though it doesn't detail ID format or validation rules.

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 purpose with specific verbs ('compare multiple collections side by side') and resources ('collections'), and distinguishes it from siblings by focusing on comparison rather than discovery or retrieval. It explicitly lists what aspects are compared: temporal coverage, resolution, variable/layer info, theme, and keyword overlap.

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 provides clear context for when to use this tool ('useful for deciding which dataset best fits an analysis') and references a sibling tool for discovering IDs ('Use list_collections() to discover IDs'). However, it does not explicitly state when not to use it or name specific alternatives among the many sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.