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

The annotations already declare readOnlyHint=true and openWorldHint=true, so the description doesn't need to repeat that. However, it adds critical behavioral context: it warns that the tool returns a list of candidates to be shown to the user, that the user must choose unless exactly one match, and that the tool's output is council data that should not be treated as instructions. It also mentions that it reads by_date, indicating a dependency on another tool's output. This goes beyond annotations but could have been slightly more explicit about the read-only nature, though the annotations cover it, so a 4 is fair.

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?

The description is long but well-structured with step-by-step instructions and explicit rules. It front-loads the primary action ('Lists the properties...') and then provides necessary behavioral guidance. Every sentence earns its place, though it could be slightly more concise by removing the step numbering and breaking into paragraphs, but it's acceptable for a tool with complex user-interaction requirements.

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?

Despite being a complex tool with user-interaction and integration with other tools (like get_collections's required_input), the description is remarkably complete. It covers what the tool does, how to present results, what to avoid, and how to handle edge cases (non-exact matches, provisional results). The schema covers parameters, and annotations cover safety, so nothing essential is missing for an agent to call it correctly and interpret its output.

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 schema documentation covers 100% of the parameters, with descriptions for both 'postcode' and 'query'. The description adds value by explaining the role of the 'query' parameter (narrows a long list, never selects a property) and the purpose of 'postcode' (a full UK postcode). This is a slight enhancement over the schema, but since the schema already provides clear descriptions, a 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?

The description clearly states the tool's purpose: to list addresses at a UK postcode and show candidates to the user. It uses a specific verb ('find') and resource ('addresses at a UK postcode'), and differentiates from siblings by mentioning 'get_collections' explicitly and the required_input it needs, making it distinct from the other sibling 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?

The description provides explicit instructions on when to use the tool: to get a list of properties at a postcode, and when to let the user choose. It also gives clear rules about what not to do (never guess or choose for the user, never extend date patterns, etc.) and when to say something is provisional. This is a model example of usage guidance.

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