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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, so the tool is clearly read-only and safe. The description adds value by listing what metadata is returned (columns, types, etc.) but does not disclose other behaviors like caching, rate limits, or return format beyond the listed fields.

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 sentence with no filler. It front-loads the verb and resource, and each word contributes to understanding the tool's purpose and expected input.

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?

Despite lacking an output schema, the description explicitly enumerates the return fields (columns, types, row count, category, last-updated). For a simple, single-parameter tool with rich annotations, this is sufficient to understand the tool's functionality and output.

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% for the single parameter 'resource_id'. The description repeats the same example and explanation ('Dataset id, e.g. 3nka-59nz'), adding no new meaning beyond the schema. 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 uses a specific verb ('Get') and resource ('Nova Scotia Open Data dataset's schema + metadata'), listing the exact fields returned (columns, types, row count, category, last-updated). This clearly distinguishes it from sibling tools like 'datasets' which likely list datasets rather than their 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 implies the tool should be used when you have a resource_id and need detailed schema/metadata, but does not explicitly state when to use it versus alternatives (e.g., 'datasets' for listing, or 'search_within' for content). No when-not-to-use guidance is provided.

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