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

With no annotations, the description carries the burden of behavioral disclosure. It adds context beyond the schema by revealing that the tool filters based on a coverage threshold ('enough priced venues') and returns a count per area. It does not explicitly state read-only behavior, but the listing nature and lack of mutation verbs imply it. This is adequate for a simple tool.

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 a single, front-loaded sentence that immediately states the purpose, then adds the usage directive. There is no redundant wording or fluff. Every word contributes to understanding what the tool does and when to call it.

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 tool with one optional parameter and no output schema, the description covers the essential aspects: what areas are returned, the criterion for inclusion, and the count per area. It could mention error scenarios or the meaning of 'enough', but these are not critical for a basic list operation. The description is complete enough for an agent to call it correctly.

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 input schema already provides a clear description for the single optional parameter ('Filter to one city, e.g. 'Istanbul''), achieving 100% coverage. The tool description does not add any parameter-specific guidance, so the baseline of 3 applies – the schema does the heavy lifting.

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 states a specific verb ('list') and resource ('areas with price data') with a clear criterion: 'which Turkish districts and neighbourhoods Vahada has enough priced venues to answer for'. It also specifies the return value (number of venues per area). This is self-contained and distinct from sibling tools like venue_prices or price_index, which focus on actual prices rather than coverage.

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 explicitly directs the agent to 'Call this first when unsure whether an area is covered', which is a clear usage context. It does not name specific alternatives or exclusions, but the 'call this first' phrasing implies it is a preliminary check. Given the simplicity of the tool, this is sufficient guidance.

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