add_plant

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

Annotations already cover readOnly=false, destructive=true, and idempotent=false. The description adds value by stating that the operation changes state on Growatt's side, clarifying the external effect of the call. It does not contradict the annotations.

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 short sentences with no filler. The action is front-loaded, and the second sentence adds a meaningful behavioral note rather than repeating the schema.

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 three fully documented required parameters, a rich annotation set, and an output schema, the description provides everything an agent needs to decide and invoke the tool. Return-value details are unnecessary because the output schema exists.

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%, with all three parameters including units and source context already documented (e.g., c_user_id returned by list_users, peak_power in kWp). The description adds no parameter-level meaning beyond the schema, so baseline 3 applies.

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?

States the exact operation (create), the resource (a new plant), and the target (an end user). This clearly distinguishes it from retrieval siblings like get_plants and the mutation sibling modify_plant.

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 makes the intended use case clear: creating a new plant for an end user. It does not explicitly name alternatives or exclusion conditions, but the 'Create' verb and mention of end-user scope provide sufficient context against the sibling tools.

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