get_data

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

With no annotations, the description carries the full burden and discloses key behaviors: automatic switch from inline to file download based on payload size or force_file_download, the requirement for key_filter as a dotted SDMX string (not a dictionary), and timeout risks with long time series. This gives the agent a clear behavioral model before invocation.

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 tight sentences, front-loaded with the core purpose, then the output behavior, then two critical parameter tips. Every sentence earns its place; there is no fluff or repetition.

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 8 parameters and an existing output schema, the description covers the essential operational decision (inline vs file), the key_filter syntax pitfall, and the timeout issue, all in a compact form. The output schema and rich parameter descriptions handle the remaining details, so the description is complete for its role.

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 baseline is 3. The description adds operational depth beyond the schema: it explains the file-download trigger threshold, elaborates on the key_filter format with a concrete example, and contextualizes last_n_observations as a timeout mitigation for specific dataflows. Some information duplicates the schema, but the added usage context justifies a 4.

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 'Fetch statistical data from ISTAT', a specific verb and resource, and clearly distinguishes from sibling metadata tools (get_constraints, get_concepts, discover_dataflows) by targeting actual data retrieval. It also includes scope details like inline vs file output, making the purpose unambiguous.

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 provides clear contextual usage guidance: small queries return inline text, large datasets auto-download to a file, and force_file_download=True forces file output. It also gives an explicit troubleshooting tip (pass last_n_observations=1 for long time series to avoid timeouts). However, it does not explicitly name when-not-to-use alternatives, so it stops short of a 5.

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