rf_optimize

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does so well by explaining that the call returns a job id immediately, that trial 0 is always the analytic seed, that exploration runs at draft mesh, and that results are not verified/exported/reported unless rf_design is used.

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 compact and front-loaded: purpose first, then async behavior, then the caveat and alternative. Every sentence earns its place, and no filler is present.

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 is operationally complete for an asynchronous optimization tool: it tells the agent what happens, what to do next, and which sibling to use for verified results. Minor gaps remain around configuring `spec` and what prerequisites exist, but the sibling tools and self-explanatory parameters fill most of those gaps.

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 0%, so the description needs to compensate. It adds meaning to `spec` by referencing 'device's parameters' and clarifies the study's trial behavior, though it doesn't explicitly explain `seed`, `n_trials`, or `timeout_s`. The parameter names and defaults are largely self-explanatory, making this a solid but not exhaustive contribution.

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 action and resource: 'Start an Optuna study over the device's parameters, scored by HFSS.' It distinguishes itself from rf_design by explicitly saying to call rf_design instead when the winner should be verified, exported, and reported.

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?

It clearly tells the agent when this tool is appropriate: for exploration at draft mesh. It names the alternative, rf_design, and the condition for choosing it, while also directing the caller to poll rf_job_status after getting a job id.

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