get_data

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does reveal the return shape ('raw values with year, unit, and unit label') and clarifies that this is actual time-series data, which is useful. However, it does not mention defaults, limitations, or any side effects beyond the obvious read-only nature of 'Get'.

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 and front-loaded with the core action and resource. The example adds concrete value without unnecessary verbosity, and every sentence earns its place.

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 tool with no output schema, the description adequately covers the purpose, example usage, and return contents. It lacks explicit workflow guidance and default-behavior detail, but the schema fills most gaps, making this reasonably complete for an agent to call correctly.

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%, so the schema already explains all five parameters. The description adds context about time-series and raw values, but it does not add parameter-specific meaning beyond what the schema provides; the baseline of 3 applies.

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 a specific verb ('Get') and resource ('actual data (time series) for a variable in one or more territorial units'), and the GDP example concretely illustrates the intended use. This clearly distinguishes it from the sibling search tools, which retrieve metadata rather than data.

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 implies a workflow by referencing 'search_units' and 'search_variables' in the schema and by contrasting 'actual data' with search-oriented siblings, but it never explicitly states when to use this tool instead of get_unit_details or search tools. The intended pipeline is inferable rather than stated.

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