find_best_days

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

With no annotations, the description carries full behavioral disclosure. It explains that scoring is over hours actually spent outside (8am–6pm), uses feels-like temperature that accounts for humidity and wind chill, and that the ranking is a stated preference, not a measurement. It also discloses that each day returns supporting numbers (feels-like range, rain chance, wind, humidity) and instructs the agent to report those alongside the pick.

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 longer than average but well-structured and front-loaded with the core purpose. Each paragraph adds distinct value: usage guidance, scoring logic, and output expectations. No filler or redundancy. Slightly verbose for the simplicity of the tool, but justified by the need to explain the scoring nuances.

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?

Given there is no output schema, the description fully covers what the agent should expect and how to report results. It explains the ranking rationale, the parameters' influence, and the output format. There are no critical gaps that would leave an agent guessing how to invoke or interpret the 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 baseline is 3. The description adds meaningful context beyond the schema: it ties startHour/endHour to the outdoor hours window, explains that temperature parameters are feels-like, and clarifies that location can be omitted for home. This enhances parameter understanding without repeating schema text.

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 opens with a specific verb ('Rank') and resource ('days ahead'), and immediately clarifies the purpose: picking a pleasant day for outdoor activities. It explicitly distinguishes this from 'what is the weather', which separates it from sibling forecast tools. The contrast with 'a day they have already chosen' further disambiguates it from get_forecast.

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 provides explicit when-to-use guidance: 'Use it when the user wants a day picked out of a range — a hike, a ride, a picnic, painting the fence — rather than the outlook for a day they have already chosen.' It also states what the tool answers ('when should I go') versus what it does not. This is direct and actionable.

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