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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety profile is covered. The description adds genuine context beyond that: the provenance (police open data), the comparison window (latest year against the year before), the normalization and ranking, and the default result size. It does not say what happens on an unrecognized neighbourhood or whether matching is exact or fuzzy, which keeps it below a 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?

A single tight sentence with the subject and geography front-loaded, followed by the comparison window, unit, ranking, default behavior, and an example — every clause contributes information an agent would otherwise have to guess.

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 one-optional-parameter lookup with no output schema and rich annotations, the description covers provenance, units, ranking, default output, and an example. Only edge behavior (unknown neighbourhood names, how district-level values relate to neighbourhood rollups) is left unstated.

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% and the single parameter already documents optionality, examples, and accepts both neighbourhoods and districts. The description reinforces the example and adds the no-input default, which is useful but largely duplicative of structured data, so the baseline of 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 concrete resource and metric — bicycle and moped thefts per Amsterdam neighbourhood, from police open data — plus the unit (per 1,000 residents) and the ranking. It is immediately distinguishable from every sibling tool (conferences, jobs, markets_today, etc.), with no ambiguity about what is returned.

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 default invocation path explicitly ("no input gives the top 10") and supplies a worked example (neighbourhood='Oude Pijp'), so an agent knows a zero-argument call is valid. What's missing is any explicit exclusion or note on when a caller should instead query a different tool, though the sibling list offers no real alternative for this data.

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