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LoveMaker-art

silly-tavern-mcp

st.mvu.settings.configure

Set MVU global configuration options like model, API endpoint, update mode, and token limits via semantic fields. Requires confirmation before changes apply.

Instructions

Configure MagVarUpdate/MVU global settings through semantic fields. Requires confirm: true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
apiKeyNo
apiUrlNo
confirmNo
enabledNo
updatesNo
modelNameNo
updateModeNo
modelSourceNo
temperatureNo
snapshotLabelNo
maxChatHistoryNo
maxReplyTokensNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.11.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries the full burden of disclosing behavior. It adds one useful behavioral trait: a confirmation requirement. However, it does not explain the effects of configuring settings, whether changes are persisted immediately, whether the operation is atomic, what happens if confirm is false, or any permissions/side effects. For a mutating configuration tool, this is minimal disclosure.

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

Conciseness3/5

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

The description is short and the core purpose is front-loaded, but the brevity approaches under-specification. Given 12 undocumented parameters, no annotations, and no output schema, this level of conciseness is not 'appropriately sized'; it sacrifices necessary detail.

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

Completeness1/5

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

This is a complex configuration tool with 12 parameters, nested objects, zero schema description coverage, no annotations, and no output schema. The description only offers a general purpose and a confirm requirement. It is critically incomplete for an agent to select and invoke the tool correctly.

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

Parameters1/5

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

Schema description coverage is 0% and the description provides no parameter-level meaning. None of the 12 parameters (apiKey, apiUrl, updates, temperature, etc.) are explained, and 'semantic fields' is too vague to compensate. The agent is left without meaningful guidance on what values to supply.

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

Purpose4/5

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

The description clearly states a specific action ('Configure') on a specific resource ('MagVarUpdate/MVU global settings'). The resource name distinguishes it from most siblings and especially from st.mvu.settings.get, which is a read operation. However, 'through semantic fields' is vague and it does not explicitly contrast with other patch/configure sibling tools.

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

Usage Guidelines2/5

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

No guidance is given about when to use this tool versus alternatives like st.mvu.settings.get, st.config.patch, or st.resource.patch. The only usage hint is 'Requires confirm: true,' which is a precondition rather than a selection guideline. The description does not state when this tool is appropriate or when a different configure/patch tool should be used.

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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