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

No annotations exist, so the description carries the full behavioral burden. It does disclose the shape of what comes back ('fact ids + verification states'), which matters because there is no output schema, but it says nothing about volume, ordering, completeness, or whether results are paginated or cached.

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 front-loaded sentence with no filler or repetition. It is close to the minimum viable length, though the parenthetical '(parkinguk)' is somewhat redundant given the tool name and could have been spent on usage guidance instead.

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 trivial zero-parameter list tool, the description covers what it returns, which is the main unknown given no output schema. It stops short of explaining how the returned ids should be consumed, leaving an agent to guess that they feed into parkinguk_get_fact.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate. Baseline 4 applies; the description correctly refrains from inventing filter semantics that the empty schema does not support.

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 gives a specific verb ('List') and names the exact resource returned ('fact ids + verification states'), scoped to the parkinguk domain. An agent can distinguish it from parkinguk_get_fact and parkinguk_changes only by inferring the list/get/changes naming pattern, since the description never names those siblings explicitly.

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 when-to-use guidance, no statement of prerequisites, and no reference to the obvious alternatives (parkinguk_get_fact for fetching a single fact, parkinguk_changes for change history). The natural 'list then get' workflow is left entirely to inference.

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