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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is handled. The description adds real behavioral context beyond that: the data source switches depending on whether a station is connected, falling back to a forecast. It still says nothing about freshness, units, or rate limits.

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?

Two compact sentences: the first delivers the return payload, the second delivers the usage trigger. No filler and the content is front-loaded.

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?

With no output schema, the description does the work of characterizing the return (weather plus per-bed soil readings), and a single optional parameter needs little explanation. Only finer details such as units or how beds without sensors appear are missing.

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?

There is a single optional 'garden' parameter with 100% schema description coverage, including the default-to-first-garden behavior, so the schema carries the semantics. The description adds no additional parameter meaning. Baseline 3 applies when schema coverage is complete.

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 uses a specific verb+resource combination and enumerates the payload: current weather at a named garden plus per-bed soil moisture/temperature. It implicitly separates itself from get_forecast by including soil data and a station-vs-forecast fallback, but it never names that sibling to draw the boundary explicitly.

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?

Concrete trigger phrases are given: 'how is the garden right now / should I water'. That tells an agent when this is the right call. No exclusions or alternative tools (get_forecast, get_soil_readings) are named, so the routing is clear but incomplete.

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