search_dataset

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

With no annotations provided, the description carries the full burden and discloses the non-obvious matching semantics: all query words of 3+ characters must be present, and partial word matching applies. The empty-query fallback behavior and the German-language constraint are also surfaced. It stops short of stating rate limits, pagination, or what fields a result contains beyond "id".

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?

Front-loads the core purpose, then matching rules, then the language caveat, then the follow-up routing — a logical order with no filler. Slightly dense with line-break artifacts, but every sentence carries 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?

For a two-parameter search tool with no annotations and no output schema, the description covers the critical unknowns: matching logic, empty-query behavior, language of titles, and the ID handoff to fetch tools. The remaining gap is the shape of a result and the meaning/bounds of "limit", which an agent must discover by calling.

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%, so the description must compensate. It explains the "query" parameter thoroughly (AND-matching, 3-character minimum, empty-string meaning) but says nothing about "limit" — its default of 20 is visible in the schema, yet the maximum or cost implications are unexplained.

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?

States a specific verb and resource ("Search the OGD catalog by keyword") and explicitly distinguishes itself from the two siblings by naming them and describing the follow-up step. An agent can tell instantly this is the discovery entry point and that fetch_dataset_json/csv are the retrieval steps.

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?

Gives concrete when-to-use guidance: empty query returns recently updated datasets, and keywords must be German because titles are German (with an example contrasting "Bevölkerung" vs "population"). It also routes the agent onward by telling it to pass a result's "id" to the fetch siblings.

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