Current weather in a Philippine city

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

Annotations already declare readOnlyHint=true, openWorldHint=true and idempotentHint=false, so the safety and external-call profile is covered. The description usefully discloses the upstream provider (Open-Meteo) and, via 'major Philippine city', that coverage is limited rather than global. It still omits units (Celsius/Fahrenheit), error behavior for unknown slugs, and why results are non-idempotent (they change over time), so it adds context but not full behavioral disclosure.

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?

Two sentences, front-loaded with what the tool returns before the argument convention. Every clause carries information (metric list, source, slug format) with no filler or repetition of the title.

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?

With only two parameters, no output schema, and no nested objects, the definition is nearly complete: the parenthetical field list effectively substitutes for a missing output schema. The only real gap is the absence of unit and error-handling detail, which is a minor omission for a read-only lookup tool.

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 coverage is 100%, so the parameters are already documented and the baseline is 3. The description earns an extra point by extending the slug convention beyond the schema's two examples to five ('manila', 'quezon-city', 'cebu-city', 'davao-city', 'cagayan-de-oro'), making the lowercase-hyphenated '<city>-city' pattern obvious and reducing malformed-input risk.

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 names a specific verb+resource ('Current weather ... for a major Philippine city') and enumerates the returned fields (temperature, humidity, feels-like, rain, wind) plus the upstream source (Open-Meteo). It is unambiguously distinct from all siblings (currency, scholarships, holidays, regions, schools), so an agent can select it without opening the schema.

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 word 'Current' implicitly scopes the tool to present conditions rather than forecasts or history, and the slug examples imply how to supply the argument. However, there is no explicit when-to-use/when-not guidance and no named alternative for non-major cities or for forecasts, so the agent must infer the boundaries.

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