query_dataset

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

With no annotations, the description carries full burden. It only adds 'real data' and a code snippet, but fails to disclose read-only nature, rate limits, response format, or pagination behavior beyond what's in the parameter schema.

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?

Two sentences with no redundancy. First sentence defines purpose, second adds specific guidance. Highly efficient.

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?

No output schema and no description of return format or pagination details. While parameter schema is well-covered, the description omits what the query returns (e.g., rows, columns) and does not mention limit constraints already in schema.

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 coverage is 100% so baseline is 3. The description adds concrete filter example and dataset ID hints, adding value beyond the schema especially for the filters parameter.

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 'Query real data from a dataset', which is a clear verb+resource pair. It distinguishes from siblings like 'get_dataset_info' and 'search_datasets' by specifying 'real data', but could be more explicit about the difference.

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 provides example usage for municipal data and hints at checking instructions for dataset IDs, but does not explicitly contrast with alternatives or give when-not-to-use guidance. Usage is implied rather than directly stated.

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