generate_packing_advice

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

The description discloses that the tool uses server-initiated LLM sampling and retrieves the forecast, which implies external calls and potential latency/cost. However, it does not mention any side effects, whether it is read-only, or any required permissions. Since no annotations are provided, the description carries the burden but only partially covers behavioral aspects.

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 extremely concise, consisting of two short sentences that convey the core functionality without unnecessary verbosity. It gets straight to the point and is easy to parse.

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?

The description provides enough context to understand the basic purpose and flow (retrieve forecast, request LLM). However, it lacks parameter explanations and does not clarify how this tool differs from get_packing_context or what output format to expect. This leaves some gaps for an agent deciding whether to invoke it.

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 defines 'city' as a required string and 'days' as an integer with default 3, but the description provides no explanation of what these parameters mean or how they affect the advice. An agent would not know if 'days' refers to forecast duration, trip length, or something else. This is a significant gap given there are only two parameters.

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 tool's purpose: generate packing advice. It also explains the mechanism (server-initiated LLM sampling, retrieving forecast) which distinguishes it from pure weather tools. However, it does not explicitly differentiate itself from the sibling tool 'get_packing_context', which might also relate to packing.

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 does not provide explicit guidance on when to use this tool versus alternatives. It implies it should be used for final advice after retrieving the forecast, but there is no direct statement contrasting it with get_packing_context or other tools. An agent would have to infer the appropriate usage context.

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