singapore_query_carpark_directory

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

Annotations already cover read-only, idempotent, non-destructive, open-world, so the bar is lower. The description adds real value beyond them: it discloses that results come with source coverage from a bundled catalog and that metadata should be fetched for current coverage, which flags a potential staleness caveat an agent would not otherwise infer.

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?

Purpose and the critical dataset-ID instruction are front-loaded, and the four sentences are each doing work. The final clause about coverage/metadata is slightly dense and could be tightened, but nothing is wasted.

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?

With a full output schema present, return values need no explanation, and the description still supplies the pre-call inspection step and a coverage caveat. The only omission that matters for correct selection is disambiguation from the carpark-availability and generic-dataset siblings.

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?

Despite 50% schema description coverage, the description enumerates each capability so the agent can map them: 'exact filters' to filters, 'column text search' to q, 'fields', 'sort', 'pagination' to limit/offset. The two undocumented schema params (limit, offset) are self-explanatory and bounded in the schema, so no meaningful gap remains.

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?

States a specific verb and resource ('Query HDB Carpark Information') and pins the exact dataset ID (d_23f946fa557947f93a8043bbef41dd09), so an agent knows precisely what it retrieves. It does not, however, distinguish this static directory from the nearby sibling singapore_get_carpark_availability (live availability) or from the generic singapore_query_dataset, leaving a real ambiguity unresolved.

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?

Gives one concrete workflow step ('Inspect dataset ... first for filter fields'), which is genuinely useful before calling. But it never states when to choose this tool over singapore_get_carpark_availability or singapore_query_dataset, and offers no exclusion criteria.

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