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

With no annotations, the description carries the transparency burden. It discloses the primary data source (Open-Meteo), the fallback (wttr.in), supported city name formats, and forecast-day range/default—useful behavioral details beyond the schema.

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?

A single compact sentence packs the core action, both parameters, constraints, defaults, and source strategy with zero filler. Information is front-loaded and every phrase 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?

For a simple read-only weather query, the description gives enough to invoke correctly. It lacks an explicit statement of return format/fields, which matters because there is no output schema, but the high-level return content ('实时天气和未来几天预报') is stated.

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 0%, yet the description fully compensates: it explains that city accepts Chinese or English names, and that days accepts 1-7 with a default of 3. This is exactly the meaning an agent needs and is not present in 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?

States a specific verb ('查询' query), a concrete resource (global city weather), and a clear scope (current conditions plus multi-day forecast). Even without siblings, an agent immediately knows what the tool does.

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?

No explicit when-to-use or when-not-to-use guidance, and no sibling alternatives are named. The global-city scope and primary/fallback source hints at intended use, but the agent must infer when this tool is appropriate.

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