get_series

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

With no annotations, the description carries the transparency burden. It discloses return format ('compact [period, value] pairs plus the source institution and dataset id') and a key behavioral trait ('Omitting geography returns every region'). It could add more about pagination or error behavior, but the essentials for a safe read operation are covered.

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 three sentences, each earning its place: what it does, what it returns, and how to vary its scope. It is front-loaded with the action and resource, and the alternative tool reference is tucked naturally into the final sentence. No filler 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 there are 7 parameters and no annotations, the description covers the most important context: its role as primary data tool, return structure, and the behavior of omitting geography. Because an output schema exists, deep return documentation is unnecessary. It does not mention date handling or dimensions, but the schema already documents those.

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 coverage is 100%, so the description need not restate parameter meanings. It does add a usage hint for combining limit and geography for national comparisons, but this is more a suggestion than semantic enrichment beyond the schema's already clear descriptions. Baseline 3 is appropriate.

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 opens with a clear, specific verb and resource: 'Fetch a time series for one indicator.' It also labels itself as 'the primary data tool,' which immediately distinguishes it from sibling tools like get_snapshot or compare_series. The explicit contrast with get_snapshot ('for a single-year ranking') further reinforces its unique purpose.

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?

The description explicitly says 'This is the primary data tool,' signaling when it should be preferred. It also provides a concrete alternative: 'use get_snapshot for a single-year ranking.' It gives usage context for geography and limit ('combine with limit for national comparisons'), though it doesn't explicitly exclude other comparative tools like compare_series.

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