zurich_parking_live

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds context beyond annotations by specifying the data source (ParkenDD API), number of parking garages, and output format options (Markdown table or JSON). No contradiction with 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 presented in both German and English, which adds redundancy and length. While it is not overly long, it could be more concise by using a single language or combining the two.

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's simplicity (one optional parameter, read-only), the description covers essentials: real-time data, 36 locations, output format, and data source. It could mention limitations or update frequency, but is fairly complete.

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?

Although the schema description coverage is indicated as 0%, the schema actually contains a description for the `format` parameter. The description further clarifies by mentioning 'Markdown-Tabelle mit aktuellen Parkhaus-Belegungen (oder JSON bei format='json')', adding value beyond the schema.

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 it retrieves real-time parking occupancy data for Zurich, specifying the resource (36 parking garages) and output details. It distinguishes itself from sibling tools which are mostly about city council, air quality, or datasets, as this is the only parking-specific tool.

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 implicitly indicates usage for real-time parking data, but does not explicitly state when to use this tool vs alternatives. However, given the unique nature of this tool among siblings, the context is clear.

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