zurich_catalog_stats

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

Annotations already indicate the tool is read-only, idempotent, and non-destructive. The description adds value by detailing the kind of statistical information returned (counts, distributions), beyond what annotations provide. No contradictions detected.

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 extremely concise: two short sentences plus a return note. It front-loads purpose immediately and uses bullet-like clarity without superfluous words. Every sentence earns its place.

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 tool has no parameters, simple output, and annotations covering safety and openness, the description sufficiently explains what the tool does and returns. The presence of an output schema further reduces the need for detail.

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 tool has no parameters, and the input schema coverage is 100%. The description does not need to explain parameters, and the baseline score of 4 is appropriate as it adds no unnecessary information.

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 provides an overview of the entire Zurich open data catalog, specifying that it shows total number of datasets, category distribution, and common formats and tags. This uniquely distinguishes it from sibling tools that focus on specific datasets, searches, or other domains.

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 obtaining aggregate catalog statistics but does not explicitly state when to use this tool versus alternatives like search or specific dataset tools. There is no guidance on when not to use it or mention of prerequisites.

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