Estado del aprendizaje

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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safety profile is covered. The description adds that the payload includes sample data and model version, which is useful, but says nothing about freshness, caching, or whether it can be slow/expensive.

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 short sentence with no filler, and the key noun (aprendizaje continuo) is front-loaded. It is terse enough that the parenthetical is doing real work, though one more clause about scope would not have been waste.

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 read tool with no output schema, the description gives the essentials: it is a status read and it contains sample and model-version information. A little more on what 'estado' comprises (e.g. counts, last-updated) would make it fully self-sufficient.

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 nothing for the description to disambiguate. Baseline of 4 applies; the parenthetical does clarify the shape of the return payload rather than any input.

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 a specific resource ('aprendizaje continuo de la IA') and clarifies what the status covers ('muestras y versión de modelos'), so an agent knows it returns learning-sample and model-version info. It does not need sibling differentiation because no sibling tool overlaps with this domain, but it also doesn't name an alternative.

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 guidance on when to call this versus other status/insight tools such as get_crop_insights or get_overview. The description states what the tool is but not the situation that should trigger it.

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