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

With annotations providing only a title, the description must carry the burden of behavioral disclosure. It does disclose the data lag ('run a few days behind today') and lists the data points returned, but it omits important behavioral details such as return format, units, timezone handling, or error conditions. This is a moderate disclosure for an otherwise opaque tool.

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, well-structured sentence that front-loads the core purpose ('what the weather actually was'), specifies the inputs (location, date range), and lists outputs (average high/low, rainfall, extremes) with a note on data freshness. No words are wasted, and the dash structure improves readability without losing conciseness.

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 the tool has no output schema, the description does a good job of enumerating the key return data (average high/low, rainfall, extremes) and the temporal constraint (records lag). It could be more complete by specifying units or date formatting, but it provides enough context for an agent to select and invoke the tool correctly.

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 the parameters are already well-documented structurally. The description adds context by framing start/end as 'between two dates' and lat/lon as 'location', but it doesn't provide new per-parameter semantics beyond what the schema states. A baseline of 3 is appropriate when schema does the heavy lifting.

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 retrieves actual historical weather at a location between two dates—'what the weather actually was'—and specifies the metrics returned (average high/low, rainfall, extremes). This distinguishes it from sibling tools like weather_forecast, which predict future conditions, and weather_marine/air, which focus on different domains.

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 phrase 'actually was' implies historical data vs. forecast, and 'Records run a few days behind today' gives a concrete usage constraint. It provides clear context for when to select this tool, though it does not explicitly name alternatives like weather_forecast or state when not to use it.

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