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

Annotations already declare read-only, idempotent, open-world, non-destructive. The description adds beyond that: verify=true performs live upstream checks per matched dataset (a latency/cost trait), and the Open Data API has no listing endpoint of its own, which explains why this tool must exist. It stops short of stating failure behavior when an upstream call fails.

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 what the tool returns and its authority claim, then the routing rationale, then search hints. Dense but largely waste-free; the parenthetical example list of opaque names is slightly long but earns its place by illustrating the problem.

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?

With no output schema, the description carries the return-value burden and does so: it says each entry includes contents, update frequency, file format, and newest-file timestamp. Combined with full schema coverage and rich annotations, an agent has what it needs; only edge-case/failure behavior is unaddressed.

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 all three parameters (limit, search, verify) are already documented with defaults, max values, and cost implications. The description adds only example search keywords, which the schema's own examples and search description already cover; baseline 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?

States a concrete verb+resource — datasets from the KNMI Data Platform — and enumerates the payload: contents, update cadence, file format, and live newest-file timestamp. It also names the sibling it feeds (knmi_dataset_files) and the opaque-name problem that distinguishes this listing tool from the file-fetching tools.

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?

Explicitly framed as the 'AUTHORITATIVE starting point for Dutch weather and climate data' and instructs the agent to use it to obtain the exact dataset name/version string that knmi_dataset_files requires, explaining why (opaque names, no upstream listing endpoint). It even supplies suggested search terms.

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