plan_calibration

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

With no annotations provided, the description carries the burden of behavioral disclosure. It clearly states that unanswered facts become open questions, which is a key behavioral trait. It also explains the meaning of three boolean parameters, adding valuable context. It does not mention side effects or permissions, but as a planning tool those are likely minimal.

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 structured into a brief opening statement followed by parameter explanations. It is fairly concise and front-loaded, but the parameter explanations take up several lines. Every sentence adds value, and there is no fluff, though it is slightly longer than strictly necessary.

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 output schema exists, so the description need not explain return values. The description provides useful context for the three booleans and the open-question behavior, but it leaves the 'request' parameter and the role of material_model/n_uncertain_parameters under-specified. Overall, it is adequate but has clear gaps for a 6-parameter tool with no schema descriptions.

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 schema has 0% description coverage, so the description must compensate. It clarifies the semantics of uncertainty_required, quofem_wrappable, and screened well, but leaves request, material_model, and n_uncertain_parameters without any explanation. The names are somewhat self-explanatory, but the description only partially compensates for the total lack of schema-level documentation.

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 tool's function: 'Plan a calibration study from the method matrix.' This is a specific verb+resource combination that distinguishes it from general simulation planning. However, it does not explicitly contrast with the sibling tool 'calibration_options', so there is some ambiguity about how they differ.

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 instruction 'Pass what you know; unanswered facts come back as open questions' gives a practical usage pattern and explains the tool's behavior with partial inputs. However, it does not explicitly state when to use this tool over alternatives, nor when not to use it. The usage context is implied rather than fully articulated.

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