get_climate

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

With no annotations, the description carries the burden and does well: it discloses that only devices reporting temperature/humidity are included, that data comes from thermostat local_temperature and standalone sensors, and that each entry has a 'kind' field. It does not cover error handling or rate limits, but for a simple read tool this is sufficient.

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 two sentences long, front-loaded with the primary action, and contains no filler. Every clause adds value: scope, device types, optional filtering, and the output 'kind' field are all relevant.

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 that an output schema exists (so return fields need not be enumerated), the description provides complete context: it explains what values are read, which devices are included, how to filter with 'id', and the meaning of 'kind'. It adequately differentiates the tool's purpose within a large sibling set.

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 only contains 'id' with no description, so the description is the sole source of parameter meaning. It explicitly states 'If id is given, return one device only', fully explaining the behavioral effect. Since there is only one parameter and it is well explained, this warrants a top score.

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 verb 'Read' and the resource 'temperature (°C) and/or humidity (%)' for relevant devices, distinguishing it from siblings like get_sensor or get_sensors by specifying device types (thermostats and standalone temp/humidity sensors) and the 'kind' field. It is specific and unambiguous.

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?

Usage context is implied rather than explicit. The description notes that without an id it reads for every reporting device and with an id it returns one device, giving clear conditional usage. However, there is no direct comparison with alternatives or explicit 'when not to use' guidance.

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