Listar datasets

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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so safety is covered structurally. The description adds the useful fact that results are a catalog of dataset metadata including sync status, but says nothing about ordering, completeness of the list, or behavior with unsynchronized datasets.

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?

A single compact sentence with no padding, and the field enumeration is front-loaded as a parenthetical. It is slightly weaker as a lead because it is a noun phrase rather than an action statement, but nothing is wasted.

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?

With an output schema present, the description need not detail return values, and it correctly covers the input side (none) plus the general shape of entries. It falls short on the one thing that matters for a no-argument discovery tool: how it relates to describe_dataset and the domain-specific sibling tools.

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 the baseline of 4 applies; there is nothing for the description to clarify beyond confirming the call is argument-free. No schema semantics are missing.

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 names the resource ('los datasets del mirror') and enumerates the metadata each entry carries (SQL table name, description, row count, last period, sync status), so the resource is clear even though the verb is only implied by the tool name. It does not distinguish itself from the sibling describe_dataset, which an agent could easily confuse with this catalog listing.

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?

There is no statement of when to call this versus alternatives; describe_dataset and query_sql are obvious siblings that require routing guidance and none is given. The only implicit cue is that the tool takes no arguments, which a caller must infer on their own.

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