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

Annotations already mark the tool readOnly/idempotent; the description goes beyond them by disclosing that the upstream index only covers Datasets, that Concept/DataService filters return zero results, and that the server caps the limit because upstream ignores paging. This is exactly the context annotations cannot express.

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?

Although relatively long, each sentence adds operational value: purpose, return fields, limitation, and parameter caveats. It is organized with a clear intro, limitation callout, and compact Args list. No filler or duplication of the schema.

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?

With six parameters, an output schema, and sibling discovery tools, the description covers selection, invocation, parameter semantics, and expected returns (titles, publishers, themes, permalinks). The only aspects left implicit, such as sorting/pagination, are either addressed via the limitation or likely covered by the output schema.

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 coverage is 0%, but the Args block describes every parameter with practical detail: query includes examples and an empty-string warning, types carries the 'only Dataset works' caveat, and limit explains the 1-200 cap and server-side capping. This fully compensates for the schema's lack of descriptions.

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?

Description opens with a specific verb and object: 'Search Switzerland's national metadata catalogue for data resources,' and narrows the tool's role as 'the primary entry point' for discovery. It explicitly distinguishes itself from dataset-specific lookups ('before looking for a specific dataset') and from type-specific siblings by stating which entity types are unsupported. This leaves no ambiguity about what the tool is for.

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 states when to use ('find out who publishes data on a topic before looking for a specific dataset') and what NOT to use it for via the known limitation. It explicitly routes Concept and DataService searches to list_concepts and list_data_services. The empty-query warning also sets expectations around acceptable use.

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