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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=false, so safety is covered. The description adds genuine behavioral value beyond that: it discloses the paginated list return shape and the exact fields and their types, which the annotations do not carry.

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?

Three compact sentences, front-loaded with the resource and grain, followed by pagination and fields. The field enumeration is dense but earns its place given there is no output schema; nothing reads as filler.

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 usefully enumerates the return fields and types and explains cursor pagination. Gaps remain around what population the data covers (national vs per-operator/station) and how it differs from the non-daily 'train_punctuality' sibling.

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 every parameter including date/date_gte/date_lte/limit/cursor is already documented in the schema. The description's mention of next_cursor maps to that existing field and adds no new syntax, format, or constraint detail, so baseline 3 applies.

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 names a specific resource and grain ('Train punctuality in Sweden per day'), which is enough for an agent to know what data comes back. It does not, however, distinguish itself explicitly from the sibling tool 'train_punctuality', leaving the day-vs-other-granularity relationship to inference.

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?

There is no statement of when to use this tool versus the similarly named 'train_punctuality' sibling, nor any note about required filters or typical query patterns. The pagination hint ('pass next_cursor to get the next page') is procedural, not guidance on tool selection.

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