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Unload Models

unload_models

Free GPU memory held by loaded image models immediately; models reload on the next request, which may take longer. Use it when you need to reclaim VRAM before other GPU work.

Instructions

Free the GPU memory held by the image models now

The models reload automatically on the next request, which then takes longer. The server also does this by itself after a period without requests.

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the side effect (memory freed), the cost (models reload on the next request, which is slower), and that this is normally automatic. It does not say whether in-flight requests are interrupted or whether all loaded models or only some are unloaded, which is a real gap for a state-changing operation.

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?

Three short lines with the action front-loaded and the consequence and default behavior following in descending order of importance. Every sentence contributes new information; nothing is padding.

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

Completeness4/5

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

An output schema exists and there are no parameters, so the description only needs to cover behavior, which it does: effect, reload penalty, and automatic fallback. The remaining gap is concurrency/interruption semantics for a mutation-style tool with no annotations to lean on.

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

Parameters4/5

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

The tool takes zero parameters, so per the baseline this scores 4. Nothing in the description is needed to explain inputs, and it correctly mentions a scope qualifier ('the image models') rather than implying any selectable argument.

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?

States a specific verb and resource: 'Free the GPU memory held by the image models'. No sibling tool (generate_image, upscale_image, list_models, server_status) deals with memory lifecycle, so the purpose is unmistakably distinct without needing an explicit comparison.

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

Usage Guidelines4/5

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

'Free ... now' plus the note that the server already does this automatically after an idle period implicitly tells the agent that manual invocation is only warranted when memory must be reclaimed immediately. That is clear context, but it stops short of an explicit when-to-use / when-not-to-use statement or escalation guidance.

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