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

There are no annotations, so the description carries the behavioral transparency burden. It communicates a read-only forecast lookup via 'Get' and adds the 15-day maximum, but it does not disclose response shape, potential errors, timezone behavior, or whether any authentication is needed. For a simple read operation this is acceptable but not thorough.

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 sentence with no wasted words. It front-loads the verb and resource and immediately gives the key constraint of 15 days.

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 weather lookup with three fully documented parameters, the description is largely complete and an agent can invoke the tool correctly. The only notable gap is that there is no output schema and the description does not hint at the shape of the returned forecast payload.

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%: location, days, and units are all clearly documented in the input schema. The description adds no additional parameter meaning, which is acceptable because the structured schema already handles the documentation fully.

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 explicitly states the action ('Get'), the resource ('daily weather forecast'), and the scope ('up to 15 days'). This clearly distinguishes it from the sibling tool weather-get_hourly without requiring any additional inference.

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 'daily' and the tool name imply that this is for day-level forecasts rather than hourly ones, which is useful context. However, the description does not explicitly state when to use this tool versus weather-get_hourly or provide any exclusion criteria.

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

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

With no annotations, the description carries the full burden of behavioral disclosure. It states the scope (hourly, next 12 hours) and implies a read-only operation, but does not mention return format, error behavior, or data source limitations. It is adequate but not rich.

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 concise sentence with no filler. It front-loads the core action and scope, making it easy for an agent to process quickly.

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 two-parameter tool, the description is largely complete: it states the forecast type, granularity, and time window. It does not describe the return payload, but no output schema exists and the tool's purpose is straightforward enough that an agent can infer expected weather data fields.

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%, so both parameters are already documented in the schema. The description adds no additional parameter-level details beyond what the schema provides, so the baseline score of 3 applies.

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 uses a specific verb ('Get') and resource ('hourly weather forecast') with a clear time bound ('next 12 hours'). This clearly distinguishes it from the sibling tool weather-get_daily, which is for daily forecasts.

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 time range and 'hourly' granularity imply when to use this tool, but the description never explicitly names the alternative or states when to choose it instead. The guidance is present by inference, not direct instruction.

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