query_dataset

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

With no annotations, the description must carry the full behavioral disclosure burden. It mentions 'decode' but does not explain what that entails (e.g., converting codes to labels), nor does it mention read-only nature, return limits, pagination, or error behavior. This is insufficient for a query tool.

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 a single, concise sentence that front-loads the core purpose and key features (dimension filters, NUTS controls). It contains no filler or redundant information.

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?

The tool has 7 parameters and an output schema, so the description needn't explain return values; however, it is terse about what 'decode' means and how this tool differs from similar siblings like download_dataset_to_sql. It provides basic context but lacks enough detail for a complex 7-param tool.

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 baseline is 3. The description adds no parameter-level detail beyond what the schema already provides, though it hints at filters and NUTS controls which map to specific parameters. It does not elevate the meaning.

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 clearly states the tool queries and decodes statistical observations from a Eurostat dataset, with specific mention of dimension filters and NUTS controls. This distinguishes it from sibling tools like search_datasets (searching for datasets) and get_dataset_info (metadata retrieval).

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 usage for retrieving observations with filtering, but does not explicitly state when to use this tool over siblings or mention alternatives. There is clear context but no exclusions or comparisons, so it earns a 4 per rubric.

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