get_outfit_recommendation

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

There are no annotations, so the description carries the full burden. It explains that the tool analyzes four factors to generate a recommendation, which provides some transparency about its internal logic. However, it does not disclose potential side effects, dependencies on external services, or what happens if data is unavailable. For a simple get-type tool, this 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 two sentences with no filler. The first sentence immediately states the tool's purpose, and the second clarifies the analysis logic. Every word 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?

No output schema is present, and the description does not describe the return format (e.g., text vs. list of items) or any edge cases. It covers the core functionality and inputs but leaves the exact response shape ambiguous. Given the moderate complexity, this is acceptable but not complete.

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 has 100% description coverage, so parameters are well documented. The description's mention of 'location, destination, travel time' maps to origin/destination/hours_until_departure but adds no extra semantic detail beyond what the schema already provides. Baseline 3 is appropriate.

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 'Get clothing recommendations' with a specific verb and resource, and explains the inputs it uses ('current location, destination, travel time, and weather forecast'). This distinguishes it from sibling tools like get_weather_forecast and get_travel_info which focus on single data types.

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: when you need clothing advice informed by weather and travel plans. It does not explicitly name alternatives or exclusion scenarios, but the distinct purpose ('suggest what to wear') is clear enough for an agent to choose this over the weather-only or travel-only siblings. However, it lacks explicit 'when not to use' guidance.

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