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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds that results carry plan requirements, which is useful pre-call context, but says nothing about size, format, or whether the whole catalog is returned in one response.

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?

One front-loaded sentence that states the resource and its payload with no filler. The parenthetical source attribution is minor but harmless.

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 zero-parameter, no-output-schema catalog, the description is sufficient: it tells the agent what the records contain and that a plan requirement is included. Only the return format and volume are left unstated, which is a small gap for a tool this simple.

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?

The tool takes zero parameters, so there is no parameter semantics to document; the baseline for a no-arg tool is 4. The description correctly implies the call is unconditional and unfiltered.

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 gives a concrete resource and enumerates the fields returned (path, parameters, required plan), so an agent knows this is a metadata index of all datasets. It is clear on its own, but it never contrasts itself with the sibling dataset_detail, so differentiation is left to inference.

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?

Usage is only implied: a 'list of every dataset' suggests a discovery step before drilling into dataset_detail, but the description never says so explicitly, nor does it state when-not to use it. No prerequisites or alternatives are named.

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