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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description's additional context about the CKAN source and the contents of the metadata adds value beyond the annotations. It stops short of disclosing rate limits or error behavior, but given the rich annotations, this is acceptable.

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 begins with the source and purpose, then lists the metadata fields. Every word contributes without redundancy.

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?

This is a simple one-parameter tool with annotations covering safety and an output schema available. The description provides enough context about the tool's niche and parameter semantics to enable correct selection and invocation.

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?

With zero schema description coverage, the description compensates by explicitly stating that 'id' accepts a dataset ID or slug, which aligns with the example and clarifies the parameter's meaning beyond the bare string type.

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 retrieves full metadata for a dataset by ID/slug, and enumerates the included fields. It differentiates from sibling tools like package_search and package_list by emphasizing metadata completeness for a single dataset.

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 intended use case (getting detailed metadata for a specific dataset), but does not explicitly contrast it with alternatives such as package_search or package_list. The context is clear, though no exclusions are stated.

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