optimizer_setup

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

With no annotations, the description carries the full burden and does so well: it warns that every optimizer parameter must have min and max bounds, states that options are validated against the algorithm, explains server-side serialization/queueing, and describes the failure mode (call stops and reports which field failed). This goes well beyond a generic 'set fields' statement.

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 long but information-dense; the core purpose, prerequisite, and critical warning come first, with algorithm-specific option tables at the end. Every section earns its place, and the bullet-style structure makes the compatibility rules scannable.

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 complex tool with no annotations and no output schema, the description covers the essential context: prerequisite creation, critical bound constraints, failure behavior, queueing, and option compatibility. The only minor omission is detailed guidance for the remaining algorithm codes (B/G/Q/I) beyond the four common ones, but this does not block correct invocation for the documented cases.

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 coverage is already 100%, so the baseline is 3, but the description adds real value: it turns the flat options schema into a per-algorithm compatibility map (e.g., Random uses Rand Iters NOT Max Iters) and stresses the min/max bound requirement for Parameters. This materially improves an agent's ability to populate the parameters/options objects correctly.

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 a specific verb ('Configure') and resource ('an Optimize Transform') and explicitly frames it as replacing multiple transform_set_optim_field calls. The description enumerates the exact fields set (Algorithm, Error type, Inputs, Parameters, Options), making the tool's scope unmistakable and distinct from sibling transform functions.

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?

Clearly states the prerequisite: transform must already exist with Function='Optimize', and directs the agent to transform_create with transform_type='Optimize' first. It also identifies transform_set_optim_field as the alternative this tool replaces, and gives algorithm-specific option guidance so the agent knows what to send.

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