zurich_search_datasets

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable context: uses CKAN/Solr full-text search over titles, descriptions, tags, and metadata, and returns a Markdown-formatted list of summaries. This goes beyond annotations.

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 very concise: a one-sentence purpose, then a sentence about the search engine, and a return format line. No wasted words; front-loaded with the core action.

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 the annotations and rich input schema, the description covers the search functionality well. It mentions return format (Markdown list) and search capabilities. Minor gap: no mention of pagination behavior beyond schema parameters, but offset/rows are described there.

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 description itself does not elaborate on parameters, but the input schema provides rich descriptions for all 5 parameters (query, rows, sort, offset, filter_group) with examples and constraints. Baseline 3 is appropriate as schema already covers semantics well.

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 searches the Open Data catalog of Zurich for datasets. It specifies the search engine (CKAN/Solr) and scope (900+ datasets). This distinguishes it from sibling tools like zurich_get_dataset (retrieve specific) and zurich_list_categories.

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 keyword searches but provides no explicit guidance on when to use this tool vs alternatives like zurich_datastore_query or zurich_sparql. It does mention Solr syntax for advanced queries, which is helpful, but lacks when-not-to-use or conditions.

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