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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: it analyzes NOAA 7-day forecast data, applies specific thresholds (25 mph wind, 32°F freeze), returns a risk tier and high-risk days, and discloses the data source (NOAA National Weather Service) and cost ($0.10 USDC per call). It doesn't describe pagination or exact response format, but for a read-only risk assessment tool, the disclosed behavior is strong.

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 information-dense but not bloated. It front-loads the use case, then explains the analysis, gives an example, and ends with source and cost. The example is useful but slightly long; the cost disclosure is a nice touch. Every sentence earns its place, though the example could be trimmed slightly without losing value.

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?

For a read-only tool with 100% schema coverage and no output schema, the description covers the key context: when to use, what data is analyzed, what thresholds are applied, what output to expect (risk tier and high-risk days), and the data source. The only minor gap is that it doesn't specify the exact output format or units, but the example compensates. The cost disclosure is an extra contextual bonus.

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 schema already documents all three parameters (lat, lon, location) with descriptions. The description adds context about how the parameters relate to the analysis (e.g., 'US project site') but doesn't add new parameter-level meaning beyond the schema. Baseline 3 is appropriate when the 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 states a specific verb ('get'), a clear resource ('weather delay risk'), and the exact analytical scope: NOAA 7-day forecast data against construction delay thresholds (precipitation probability, wind >25 mph, freeze <32°F). It distinguishes itself from siblings like get_climate_risk_score and get_storm_event_history by focusing on construction delay risk with a concrete example. The example (Chicago IL project site) makes the purpose unmistakable.

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 explicitly says when to use it: 'when scheduling outdoor construction work, planning equipment deployment, or assessing weather risk for any US project site.' It also gives a concrete example of how to apply the output ('Reschedule concrete pours and crane operations'). While it doesn't name sibling alternatives explicitly, the use cases are specific enough to route an agent correctly among the many weather/climate siblings.

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