Valores distintos de una columna

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

Annotations already cover read-only, idempotent and non-destructive, so the bar is lower, yet the description adds real context: the default scoping to the latest period (where categories are usually complete), the row-scan cap under all_periods, and the INDEC_API_TOKEN requirement. It does not describe the return shape (ordering, deduplication) or what happens when max_rows truncates results.

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?

Three compact sentences with zero waste: purpose and use case first, then the default-vs-all_periods behavior, then the auth requirement. Front-loaded and easy to scan.

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 5-parameter tool with no output schema and low schema coverage, the description covers scoping, row limits and auth but omits how filters interact with the distinct-value computation and what the result looks like. Adequate to call correctly in the common case, incomplete for the parameterized cases.

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?

Schema description coverage is only 20% across 5 parameters, so the description must compensate. It does explain the interaction of all_periods and max_rows and the default period behavior, but says nothing about filters (the most semantically complex parameter) or the dataset/column pairing beyond what the schema enum and field descriptions already provide.

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?

States a specific verb and resource: list distinct values of a column, plus a concrete use case (discovering regiones, rubros, sectores before filtering). That distinguishes it implicitly from indec_query_dataset, indec_aggregate and indec_describe_dataset, though no sibling is named.

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?

Gives clear when-to-use guidance ('útil para descubrir ... antes de filtrar') and explains the two operating modes (default: last period only; all_periods=true: scan up to max_rows). No explicit exclusions or pointers to the alternative tools for other exploration needs.

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