get_land_cover

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

With no annotations, the description carries the transparency burden. It discloses the output structure (3-digit CLC code, label, group, exclusion flag) and the auth requirement ('No API key'), though it does not describe error handling or behavior for out-of-coverage points.

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?

All five sentences serve a distinct purpose: purpose, returns, coverage, exclusion, auth. No filler or redundancy; the core purpose is front-loaded.

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?

For a simple point-lookup tool, the description explains return values and limitations sufficiently. The absence of an output schema is compensated by the explicit list of return fields, though it could mention how to interpret the planning-exclusion flag.

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 100%, so baseline is 3. The description adds no parameter syntax details beyond the schema; it does reinforce the country restriction, but that is already in the schema's country description.

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 opens with a specific verb+resource: 'Land-cover classification for a point using CORINE Land Cover 2018.' It clearly distinguishes from sibling tools by naming the data source and return fields, including the planning-exclusion flag.

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 geographic context with 'EU27 + EEA/EFTA only' and explicitly excludes Great Britain, indicating when the tool is not applicable. However, it does not name an alternative tool within the description itself; the alternative is only present in the input schema.

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