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

Annotations already declare read-only and non-destructive, so the safety profile is covered. The description adds useful behavioral context: results come from 'OTHER portals' and relations are 'computed by thematic similarity,' which explains the tool's logic beyond the annotations.

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 two sentences, front-loads the core action ('Find related datasets from OTHER portals'), then gives an example and methodology. No redundant information; every sentence earns its place.

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 one-parameter tool with no output schema, the description provides the purpose, an example scenario, and the underlying computation method. Combined with strong annotations, this is fully complete for an agent to select and invoke the tool correctly.

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 schema documents the single parameter dataset_id with a clear description ('Dataset ID to find related datasets for. Obtained from search_datasets.'). The tool description does not add additional parameter semantics, but with 100% schema coverage, the baseline of 3 is appropriate.

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 uses the specific verb 'Find' and identifies the resource as 'related datasets from OTHER portals.' It provides concrete examples (air quality suggesting traffic or emissions data), clearly distinguishing it from sibling tools like search_datasets.

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?

It states the use case: 'Great for discovering complementary data' and illustrates when it's appropriate (e.g., looking at air quality from Generalitat). It does not explicitly mention when not to use it or name alternative tools, but the context is clear.

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