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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is established. The description adds scoping (Loire-Atlantique datasets) and query capabilities, but not richer behavioral context such as result size limits, error cases, or data freshness. This is consistent with the annotations and adds mild value above them.

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 a single, front-loaded sentence that names the tool's purpose and immediately enumerates its capabilities. Every phrase earns its place; there is no fluff, restatement, or unnecessary detail.

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 an 8-parameter query tool with a fully documented schema and examples, the description is sufficiently complete: it establishes the target resource, query language, and available operations. It does not describe output shape, but given the arbitrary select/aggregate capabilities and rich schema, that is acceptable. An explicit pointer to search_datasets as the source for dataset_id would make it slightly stronger.

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 100%, so the schema fully documents each parameter. The description groups related parameters into capabilities (filter, aggregate, sort, paginate), which is useful for orientation, but it does not add meaning beyond the schema's own parameter descriptions and examples.

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 a specific verb ('Query records'), a specific resource ('Loire-Atlantique Open Data dataset'), and the query language (ODSQL), followed by the concrete operations it supports. This clearly separates it from sibling tools like search_datasets or dataset_info, which focus on discovery/metadata rather than record-level querying.

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 makes the context clear: use this when you need to query records within a known Loire-Atlantique dataset using ODSQL. It does not explicitly name alternatives or state when not to use it, but the scope is specific enough that an agent can infer the intended use from the dataset_id prerequisite.

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