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

With no annotations, the description discloses the return payload (dataset names, IDs, descriptions, column names, links) and the search scope. However, it does not mention potential rate limits, permission requirements, or any edge-case behaviors, leaving some ambiguity about side effects and constraints.

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 three sentences, each earning its place: it states the action, lists the return values, and gives workflow guidance. There is no redundant or filler content.

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 a tool with five parameters, no output schema, and no annotations, the description is quite complete: it covers purpose, returns, and downstream usage. It only misses explicit details about response pagination behavior or empty-result handling, but the schema documents offset/limit, and the workflow is clear.

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% and every parameter has a descriptive explanation with examples. The description adds no extra parameter semantics beyond what the schema already provides, so the baseline score of 3 applies.

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 clearly states that this tool searches the Nova Scotia Open Data catalog by keyword, category, or tag. It also differentiates from siblings by explaining the workflow with list_categories and query_dataset/get_dataset_metadata.

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 explicitly instructs users to run list_categories first to get valid category/tag names, and to use the returned dataset ID with query_dataset or get_dataset_metadata for further exploration. This provides clear when-to-use guidance and a workflow.

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