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

Annotations mark the tool as readOnly, idempotent, non-destructive. The description aligns and adds useful behavioral context: it specifies the search source (Dutch government open data catalogue), that results are from CKAN, and the language behavior. No contradictions and adds value beyond 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?

Two sentences: first defines the tool's action and return, second adds language nuance. No filler, front-loaded, every sentence contributes meaning.

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 search tool with 5 parameters and no output schema, the description covers key aspects: source, return type, language behavior. Further details like pagination or empty results are not critical here. Annotations already cover safety. Overall complete enough.

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 coverage is 100% with descriptions for all five parameters. The description does not add additional semantics beyond what is in the schema, so a baseline of 3 is appropriate. The examples in the schema provide usage context.

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?

Description clearly identifies the tool as searching the data.overheid.nl catalogue of Dutch government open data, specifying the underlying CKAN package_search API and that results include titles/descriptions mostly in Dutch. This distinguishes it from sibling tools like deep_research or search_within which are broader or different domains.

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?

Provides guidance on language use: 'Query may be Dutch or English; Dutch matches more.' This helps the agent choose appropriate queries. However, it does not explicitly state when to use this tool versus alternatives (e.g., for non-Dutch data use deep_research), but the context of Dutch government data is implicit.

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