env_hydro_stations

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

Annotations already declare readOnlyHint and idempotentHint. The description adds rich context: the BAFU operates ~260 stations, 10-minute measurement interval, API failure fallback, and match_type behavior. No contradictions.

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 compact (6 sentences), front-loaded with purpose, and includes structured sections for use case and notes. Every sentence adds value, no 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 list tool with an output schema, the description covers all necessary aspects: purpose, parameters, use case, error handling, and fallback. It is complete for its complexity.

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 input schema provides descriptions for all parameters, but the description adds context (e.g., 'response_format: markdown oder json') and explains filtering usage. With high schema coverage, baseline is 3; the concise restatement and additional context earn a 4.

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 states 'Listet hydrologische Messstationen des BAFU an Schweizer Flüssen und Seen auf', clearly specifying the verb (list), resource (hydrological stations), and scope. It distinguishes from siblings like `env_hydro_current` through the use case.

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 `<use_case>` tag explicitly describes when to use this tool: to find stations by canton/water body, then call `env_hydro_current` for data. It also notes fallback behavior and empty result handling, providing clear guidance.

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