Search Datasets

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

The description discloses key behavioral traits: it only searches open datasets, and it has two modes with distinct matching behavior. Semantic mode handles synonyms and other languages, lexical does exact matching. Since there are no annotations, this is helpful context, but it omits details such as pagination behavior or rate limits, which are often relevant for search tools.

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 sentences long and front-loads the purpose. It succinctly explains the two modes and provides usage guidance without extraneous words.

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 nine parameters and no annotations or output schema, so the description needs to be quite thorough. It covers the core purpose and search modes, but it does not explain the majority of the parameters or the structure of the returned list. This leaves significant gaps for an agent trying to invoke the tool 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?

The input schema has nine parameters with zero descriptions, so the description must compensate. It explains 'search_mode' (semantic vs lexical) and implies the 'search' parameter, but leaves limit, offset, refine, exclude, order_by, timezone, and include_app_metas entirely unexplained. Given the low schema coverage, this is insufficient.

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 a specific action ('Search and list available open datasets') and identifies the source ('data.bs.ch'). It distinguishes itself from sibling tools by being the plural search tool, while 'get_dataset' implies retrieving a specific dataset. The two search modes further clarify its purpose.

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 explicit guidance on when to use each search mode: 'Use semantic for conceptual discovery, lexical for precise term/name lookups.' This is clear context, but it does not explicitly mention when to prefer sibling tools like 'get_dataset' for fetching a specific dataset, though the purpose implies the distinction.

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