sbb_list_datasets

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

Annotations already cover safety (read-only, idempotent, non-destructive). The description adds value by specifying the return type ('str') and the schema of the returned list, including fields like dataset_id, title, records_count, update_frequency, and themes. This goes beyond annotations and helps the agent understand what to expect.

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 concise, with a clear structure: a brief purpose statement, a line about return fields, and a structured 'Returns' section. Every sentence adds value without 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?

For a simple list tool with no parameters and no output schema, the description is complete. It explains what the tool does, what it returns, and when to use it, fully covering the agent's needs.

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?

Since the tool has zero parameters, there is nothing to explain. The description correctly implies that no input is needed, and the baseline of 4 applies because the description does not obfuscate or add unnecessary parameter detail.

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 lists all available SBB Open Data datasets from data.sbb.ch, using a specific verb ('listet') and resource ('Datensätze'). It also explicitly mentions the return fields, distinguishing it from sibling tools that fetch specific data types like passenger frequency or rail disruptions.

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 clear context for use: 'Nützlich zur Übersicht und Entdeckung neuer Datensätze' (useful for overview and discovery). It does not explicitly list exclusions or alternatives, but the use case is evident enough to guide an agent.

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