list_locationsReturn canonical KKTC city slugs plus districts represented by active Evlek sale or long-term-rent listings. Live inventory-location facts only; holiday-home inventory remains unavailable.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | Optional — limit districts to a single city slug. |
| Name | Required | Description | Default |
|---|---|---|---|
| cities | Yes | ||
| dataSource | No | ||
| isEstimate | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnlyHint, openWorldHint, destructiveHint), the description adds valuable context: data is derived from live Evlek sale and long-term-rent listings, and holiday-home inventory is explicitly excluded. This clarifies the tool's data coverage and currentness.
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 two sentences, front-loaded with the action verb 'Return', and each sentence earns its place: the first defines the output, the second adds a necessary data-scope qualifier. There is no redundant or extraneous text.
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 simple tool with zero required parameters, one optional parameter, strong annotations, and an output schema, the description covers the key facts: what is returned, the data source, and exclusions. It lacks explicit use-case guidance but is otherwise complete for its scope.
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 already fully documents the only parameter 'city' with an enum and description. The tool description reiterates the concept of city slugs but does not add material semantics beyond the schema, so a baseline score of 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 returns 'canonical KKTC city slugs plus districts' from active Evlek listings, using a specific verb and resource. This distinguishes it from sibling tools like get_district_profile or suggest_neighborhood by emphasizing its role as a source of valid slug data.
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 implies this tool is used to obtain canonical location slugs for querying other tools, but it does not explicitly state when to use it over alternatives or exclude inappropriate cases. No sibling tool is referenced, so usage guidance is only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools have overlapping purposes: fetch and get_listing_detail both return full listing details (differing only by ID type), and search and search_listings both perform listing searches (differing by query style). The payment_plan tool is misleadingly named as it only converts currency, not plan payments.
Most tools follow a verb_noun pattern (compare_cities, get_listing_detail, search_listings), but exceptions like fetch, search, payment_plan, and student_housing break the pattern. The mix is readable but not fully consistent.
14 tools is within the typical well-scoped range, but the set includes redundant pairs (fetch/get_listing_detail and search/search_listings) that could be consolidated, making it feel slightly inflated for the actual functionality.
The server covers core discovery (search, get detail), aggregate pricing (index, district, city comparisons), and specialized calculations (yield, student housing). As a read-only property search server it is fairly complete, though it lacks explicit filter/list-by-type tools beyond search_listings.