singapore_query_land_area

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

Annotations already declare readOnlyHint=true, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds one real behavioral caveat — source coverage comes from a bundled catalog and metadata should be fetched for current coverage — but it does not explain staleness semantics, result ordering, or what constitutes a match for the text search.

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 first sentence front-loads identity and provenance, followed by the inspect prerequisite, capability list, and a caveat — a sensible ordering. The capability sentence ('Supports exact filters, column text search, fields, sort and pagination') is largely a restatement of the visible schema and is the only real padding.

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 an output schema and rich annotations already supplied, the description only needs to carry identity and routing context, which it does, and the pointer to inspect the dataset compensates for the unknown filter fields. It falls short of complete because it never says what the rows represent (geographic breakdown, time granularity) so an agent cannot confirm suitability without inspecting first.

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?

Schema description coverage is 50%, and the description maps concepts to parameters ('exact filters', 'column text search', 'fields', 'sort and pagination'), which roughly covers all six. It adds no format semantics beyond the schema — e.g. whether 'q' is a substring or token match, or how 'sort' interacts with 'filters' — so the 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 names a specific verb ('Query') and a specific resource ('Land Area (As At December), Annual' from Singapore Department of Statistics) plus a topic tag, so the agent can tell it apart from generic siblings like singapore_query_dataset. It is clear what is being queried, though it does not describe the actual breakdown/dimensions of the dataset beyond its title.

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 instruction to 'Inspect dataset d_0b2c... first for filter fields' gives a concrete prerequisite workflow step, which is genuinely useful. However, it never states when an agent should prefer this tool over the generic singapore_query_dataset or singapore_inspect_dataset, and offers no exclusions or alternative-routing guidance despite dozens of sibling query tools.

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