enaho_listar_datasets

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

Annotations already establish read-only and idempotent behavior. The description adds context that these datasets are pre-prepared and can save time, plus notes that the `nombre` identifier is integrated with other tools. This goes beyond basic safety traits and provides useful behavioral context.

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 compact, front-loaded with the core purpose, and every sentence adds value. The first sentence states what the tool provides, the second gives usage guidance and cross-tool integration. No fluff or 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?

Given the tool's simplicity (no parameters), rich annotations, and presence of an output schema, the description covers all necessary context. It explains what the datasets contain, when to use the tool, and how to use its output (`nombre`) downstream. This is complete for a listing tool.

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?

There are zero parameters, so the baseline is 4 per instructions. The description adds clarity about the output by listing the fields (year, source modules, level, size) and explaining the `nombre` identifier's role in other tools, which is useful even though parameters are absent.

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 lists already-prepared datasets with attributes like year, source modules, level, and size. It uses the verb 'listar' implicitly through the resource description, and it distinguishes itself from other tools by focusing on pre-built parquet files rather than downloads or unions.

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?

Provides clear guidance to start here when resuming a session, explicitly stating that it can save download and union work. It also mentions that the `nombre` field is accepted by other tools, implying a workflow. However, it does not explicitly name alternatives or give a 'when-not-to-use' scenario.

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