search_datasets

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

With no annotations, the description carries the burden of describing behavior. It does disclose the return fields (code, title, period) and signals that this is only a precursor to get_structure, but it does not mention limit behavior, pagination, or failure cases.

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 short sentences front-load the purpose, state the returned fields, and give the required next step. There is 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?

The description provides the essential purpose, return fields, and follow-up call, but it omits the meaning of limit and does not disambiguate from search_indicators. This is adequate for a simple search tool with an output schema but not fully complete.

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 0%, and the description only clarifies that query is a full-text search term. The limit parameter is not explained anywhere, so the description does not compensate for the missing parameter documentation.

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 'Recherche full-text dans le catalogue Eurostat (~7000 datasets)', giving a specific verb, resource, and scope. It also states what the tool returns, but it does not explicitly differentiate from the sibling search_indicators.

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?

It gives clear workflow guidance by instructing the agent to call get_structure(code) before requesting data. The catalogue-focused scope makes the intended use case clear, but it does not explicitly state when not to use this tool or compare it with alternatives.

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