query_data

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

No annotations are provided, so the description carries full burden, and it does disclose real behavior: default measures = first 10, limit range 1-1000, offset pagination, OR within a list / AND across dimensions, and that an unfiltered dimension returns all values. It omits auth needs, rate limits, and read-only confirmation, keeping it short of 5.

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?

Front-loaded with purpose, then filter syntax, a concrete example, and an Args list. It is a bit long and the filter rules partially repeat between the prose and the Args entry, but for a complex query tool nearly 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?

Given a 7-parameter tool with 0% schema coverage but an existing output schema, the description covers purpose, filter grammar, combination semantics, defaults, and pagination. An agent has everything needed to construct a correct call without explaining return shapes that the output schema already defines.

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, which it does thoroughly. It documents all seven parameters in the Args block, including value syntax for filters, the limit range, pagination via offset, label modes, and that odata_filter is AND-appended.

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 opening line 'Haal cijfers op uit een CBS-tabel' gives a specific verb (fetch) and resource (figures in a CBS table), which is unambiguously the data-retrieval sibling among metadata tools. It only partially differentiates from siblings by deferring to list_dimension_values, so it stays below 5.

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 gives strong operational context (how filters combine, how to specify time types) and routes the agent to list_dimension_values for valid values. However, it never states explicit when-not conditions or contrasts with search_tables/get_table_measures beyond the implicit workflow.

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