OpenLandMap MCP Server

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 that the tool searches across titles, descriptions, and keywords and ranks results by relevance, which adds useful behavioral context. However, it lacks details on permissions, rate limits, or error handling, leaving gaps for a tool with no annotation coverage.

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 with clear sections (purpose, args, returns, examples) and front-loaded key information. It is appropriately sized, but the example section could be slightly more concise. Most sentences earn their place by adding 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 no annotations and no output schema, the description does a good job explaining the tool's purpose, parameters, and returns ('TopicDiscovery dict with ranked results and total found'). However, it lacks details on output structure or error cases, which would enhance completeness for a tool with such minimal structured data.

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?

Schema description coverage is 0%, so the description must compensate. It provides a dedicated 'Args' section that explains the 'topic' parameter with meaning ('Research topic in natural language'), examples, and usage context, adding significant value beyond the bare schema. This fully compensates for the lack of schema descriptions.

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 ('discover relevant datasets', 'searches across all collection titles, descriptions, and keywords') and distinguishes it from siblings by focusing on topic-based discovery rather than spatial, temporal, or collection-specific searches. It explicitly identifies the resource as 'datasets' and the action as 'discover' and 'searches'.

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 ('Given a natural language description of a topic') with examples, but it does not explicitly state when not to use it or name alternatives among siblings. It implies usage for topic-based discovery versus other tools that might handle spatial or temporal queries.

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