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remove_from_module

Remove specified variables from an existing module in a Stella model. Supply the module name and variable list to update the model structure.

Instructions

Remove variables from an existing module

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
membersYesVariable names to remove
model_idNoSession-scoped model ID. Optional; defaults to the current model for this session.
module_nameYesExisting module name
workspace_idNoOpaque application workspace handle. Required by MCP 2026-07-28 clients; supported legacy stdio clients may omit it to use the process-local compatibility workspace.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
moduleYes
model_idYes
Behavior2/5

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

Annotations already provide readOnlyHint=false and destructiveHint=false, so the agent knows it's a safe mutation. However, the description adds no extra behavioral context beyond the name, such as whether removing also deletes the variables themselves, whether the module must exist, or any side effects on dependent components. The word 'remove' could ambiguously imply deleting variables, which is not clarified.

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 sentence with no redundant words. It is front-loaded with the verb and resource, and every word adds meaning. Efficiently communicates the core function.

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

Completeness3/5

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

The tool is relatively simple (remove members from an existing module), and the output schema exists, so return values are not needed. However, the description omits important context such as whether the removed variables are deleted or just unlinked, and whether there are any prerequisites or side effects. This gap prevents a higher score.

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

Parameters3/5

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

The input schema provides 100% coverage with descriptions for all four parameters (members, model_id, module_name, workspace_id), so the description carries no parameter burden. Baseline of 3 is appropriate given the schema fully handles parameter semantics.

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 uses a specific verb ('remove'), identifies the resource ('existing module'), and specifies the object ('variables'). This clearly distinguishes it from siblings like add_to_module and delete_module, making the tool's function unambiguous.

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: when you want to remove variables from a module, use this tool. However, it provides no explicit context for when to use this over alternatives, no exclusions, and no mention of prerequisites such as the module existing or the variables being present.

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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