singapore_query_hotel_statistics

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

Annotations already declare read-only, idempotent, non-destructive, open-world behavior, so the safety bar is met elsewhere. The description adds genuinely non-obvious context: the supported query capabilities (exact filters, column text search, field projection, sort, pagination) and the caveat that coverage comes from a bundled catalog that may be stale and should be refreshed via metadata.

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?

Four short sentences, front-loaded with purpose and the dataset id before the operational workflow. No padding, though the closing coverage sentence is slightly tangential to invocation.

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?

The tool is a read-only dataset query with an output schema, so return values need no prose explanation. Given that, purpose, source, required prereq (inspect first), capability set, and a coverage-freshness caveat are all present – nothing an agent needs to call it correctly is missing.

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 only 50%: q, sort, and filters are documented in-schema, while limit, fields, and offset rely on defaults and bounds alone. The description lists the same capabilities ('exact filters, column text search, fields, sort and pagination') without adding format or syntax guidance, so it roughly matches rather than compensates for the schema.

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 Monthly Gazetted Hotels Statistics'), names the source (Singapore Tourism Board) and the topic, and pins the exact dataset id, so it is unmistakably distinct from the many other singapore_query_* siblings.

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?

It gives a real prerequisite workflow – inspect dataset d_1db0bd2ffd95ac09c66db600e60d3400 first to learn filter fields, and fetch metadata for current coverage – but never contrasts itself with generic siblings like singapore_query_dataset, singapore_search_statistics, or singapore_inspect_statistics. The when-to-use-this-instead is left implicit.

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