Get Argentina Statistics Series Data

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds genuinely useful context beyond that: no auth is required, the upstream source (apis.datos.gob.ar/series / INDEC), and the batch cap of 5 series per call.

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 sentences, zero filler, and the core action plus limits are front-loaded. Coverage of topics, source, and auth is layered after the primary action rather than padding it.

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 a 100%-covered schema, rich annotations, and an output schema, the description only needs to establish purpose, source, auth, and scope — all of which it does. Nothing needed to invoke the tool correctly is missing.

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 100% and both enums (collapse frequencies, aggregation methods) are fully documented in the schema, so baseline is 3. The description restates the resampling options and aggregation functions but adds no format or edge-case detail the schema lacks.

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?

It states a specific verb (Fetch data points) and resource (Argentine government statistics time series by ID), plus a concrete scope (up to 5 at once) that an agent can act on. It implicitly separates itself from search_series by requiring IDs, but never names that sibling in the description, so sibling differentiation is only partial.

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: fetch by ID when you already know the series identifiers. There is no explicit when-to-use vs. when-not, and the alternative (search_series) is only mentioned inside the schema's series_id description, not in the tool description itself.

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