Población: estimaciones y proyecciones (Censo 2022)

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

Annotations already declare a safe, idempotent, read-only operation, so the bar is lower; the description still adds two non-obvious behaviors: the API token requirement ('Requiere INDEC_API_TOKEN') and the default of returning the current year clamped to the dataset range when desde/hasta are omitted. It does not mention rate limits or response shape, so it is not exhaustive.

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 measure definition is front-loaded, followed by level options, temporal defaults, and the auth requirement — every sentence carries information. The parenthetical enumeration is dense but functional; nothing is redundant.

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 an 11-parameter tool with no output schema, the description covers data semantics, level granularity, defaults, and authentication well. It omits anything about the returned row shape or pagination contract (only the offset schema field alludes to 'siguiente_offset'), which matters since no output schema exists to carry that burden.

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 already 91%, giving a baseline of 3, but the description adds real meaning beyond the enum: it explains which dimensions each nivel value returns and its differing year coverage, and clarifies that desde/hasta are years (the schema only gives generic AAAA/AAAA-MM formats). Evidence: 'nivel="nacional" (por sexo y edad simple, 2022–2040)'.

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 exact measure ('Población al 1.º de julio de cada año') and enumerates the three geographic levels with their respective dimensions and year ranges, so an agent knows precisely what dataset it retrieves. It does not contrast itself with generic siblings such as indec_query_dataset or indec_aggregate, so sibling differentiation is left implicit.

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 implied through the nivel enumeration (nacional = simple ages, jurisdiccion = quinquenal groups, departamento = 2022–2035) and the default time-window rule, which effectively guides level selection. However, there is no statement of when to prefer this tool over the generic query/aggregate siblings, nor any exclusion criteria.

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