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CalWtr

relative-interpreter-mcp

by CalWtr

Create model

create_model

Set up a blank model in Relative environment and make it the current selection for subsequent operations.

Instructions

Create an empty model and select it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
descriptionNo
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses the core creation action and the fact that the new model is selected, which is a meaningful behavioral detail. However, it does not mention potential side effects like overwriting an existing model with the same name, error conditions, or what 'empty' means in terms of model contents.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence with no filler or redundancy. Every word contributes meaning: 'create' indicates the action, 'empty' specifies the initial state, 'model' identifies the resource, and 'select it' conveys the post-condition. This is appropriately concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

While the tool is simple, the lack of annotations and output schema means the description alone must cover behavior, but it omits important contextual details such as return values, error handling, uniqueness requirements, and the broader workflow implications of creating and selecting a model. Given the sibling tools include get_model, delete_model, and edit_model, more context would help an agent choose and invoke this tool reliably.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description adds no information about the 'name' and 'description' parameters beyond what the parameter names themselves imply. It does not explain uniqueness constraints, optionality of description, or any format expectations, leaving the agent to guess from bare property names.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description 'Create an empty model and select it' uses a specific verb ('create') and resource ('model') with the qualifier 'empty' that distinguishes it clearly from import_model (which creates from external data) and select_model (which selects an existing model). The action is unambiguous and immediately conveys the tool's function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for creating a brand-new blank model and makes the side effect of selection clear, which helps distinguish it from siblings like import_model or edit_model. However, it provides no explicit 'when to use' or 'when not to use' guidance, nor does it reference alternative tools by name.

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

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