swiss_avalanche_data

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The description indicates this is a data retrieval (read) operation, which is implied by 'Get', but it doesn't disclose behavioral traits like whether API key setup (swiss_set_api_key, swiss_check_setup siblings exist) is required, rate limits, or data freshness/update cadence.

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 a single efficient sentence with zero waste. It states the purpose and data source clearly. This is appropriate conciseness for a simple one-parameter tool.

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 tool with 1 param, full schema coverage, and no output schema, this is close to adequate. However, the tool touches on avalanche safety data where recency/timeliness matters, and there's no disclosure about data currency or update process. The presence of sibling setup tools (swiss_set_api_key, swiss_check_setup) suggests authentication may be needed, which isn't addressed.

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 description coverage is 100%, meaning the schema documents the single 'query' parameter with its default and description. Since there's only one parameter and it's fully covered by the schema, the description adds minimal value beyond 'Get ... data'. The baseline of 3 applies because the schema handles the documentation burden.

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 verb ('Get') and resource ('avalanche warning and snow data from SLF'). It distinguishes the data source from sibling tools. However, it doesn't quite match the level of specificity shown in top-tier examples — it doesn't clarify what specific data fields or formats are returned.

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 (avalanche/snow data needs) but provides no explicit when-to-use vs alternatives guidance. Sibling tools like swiss_weather_search_meteoswiss could overlap with weather/snow data, yet no differentiation is offered. No exclusions or context around when this tool is preferred.

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