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

Beyond the readOnlyHint and destructiveHint annotations, the description details the exact analysis logic: NOAA data, specific thresholds (25 mph wind, 32°F freeze, precipitation probability), and the output structure (risk tier + high-risk days). It also provides a concrete example output and cites the data source, giving the agent a rich understanding of what to expect.

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 four sentences and front-loads the primary use case. It includes an illustrative example and source attribution, all of which add value. While slightly longer than strictly necessary, every sentence serves a purpose and the structure is logical: use case, logic, example, source.

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 covers the tool's purpose, data source, thresholds, output format, and a worked example. There is no output schema, but the description compensates by describing the return. A minor gap is that it does not clarify how to choose between location vs lat/lon, or what happens if none are provided, even though all schema parameters are optional.

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 already provides 100% coverage with clear descriptions for lat, lon, and location, including example formats. The description adds a usage example (Chicago IL) but does not introduce new parameter meaning or clarify the optionality constraints (e.g., whether at least one input is required). It reinforces existing schema info but does not go beyond it.

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 function: it analyzes NOAA 7-day forecasts against construction delay thresholds (precipitation, wind speed, freeze events) and returns a risk tier plus high-risk days. It uses specific verbs and resources, and the example with Chicago IL makes the purpose immediately concrete. It also differentiates from siblings by focusing on short-term weather delay risk for construction, not benchmarks.

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 opens with explicit use cases: scheduling outdoor work, equipment deployment, and weather risk assessment for US sites. It gives clear context for when to use the tool. However, it does not explicitly name alternatives or when-not-to-use cases, though the sibling list (e.g., get_climate_risk_score) implies a distinction between short-term weather risk and other analytics.

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