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ComfyUI-GPU-Optimizer

ComfyUI-GPU-Optimizer

by mwaight
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

gpu_optimize

Automatically free GPU VRAM by offloading largest models to CPU until target free memory is reached. Specify target_free_mb or use auto mode.

Instructions

Automatically free VRAM by offloading models to CPU. Offloads largest models first until threshold is met. Set target_free_mb to specify how much VRAM to free, or 0 for auto.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "gpu_optimize"
  }
}

Input Schema

NameRequiredDescriptionDefault
target_free_mbNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior3/5

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

No annotations provided. Description discloses that it offloads largest models first and threshold behavior, but omits details on whether offloaded models are unloaded completely, impact on ongoing tasks, or if any state is preserved. Adequate but not comprehensive.

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?

Two concise sentences covering action, ordering, and parameter. No wasted words. Front-loaded with the core action.

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?

For a simple tool with 1 parameter and no output schema, the description covers its purpose, parameter, and behavior. Lacks info on return value or side effects, but overall adequate.

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?

Schema has 0% description coverage, but the tool description explains the parameter target_free_mb meaning and special value 0 for auto, adding significant value beyond the schema type/default.

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?

Description clearly states 'Automatically free VRAM by offloading models to CPU' with specific verb and resource. It distinguishes from siblings like gpu_offload_model (specific model) and gpu_flush_models (different behavior).

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?

Description implies usage for freeing VRAM automatically with threshold, but lacks explicit when-not-to-use or mention of alternatives like gpu_offload_model for targeting specific models. Sibling tools exist that could overlap.

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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