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list_local_models

List available ComfyUI models grouped by type. Queries the ComfyUI API or scans the models directory to show which models are ready to use before generating or downloading.

Instructions

List model files available to the connected ComfyUI, grouped by type. Read-only. Queries ComfyUI's /models REST endpoint first (works with remote ComfyUI and respects extra_model_paths.yaml — symlinked / mounted dirs the install-path filesystem scan would miss), then falls back to a filesystem scan of COMFYUI_PATH/models/ when the REST endpoint is unavailable. Size and modified time are only available on the filesystem fallback path. Use to see which models are already available before generating or downloading; use search_models to discover new models on HuggingFace, then download_model to fetch them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_typeNoFilter by model type (e.g. 'checkpoints', 'loras'). Lists all types if omitted.
Behavior5/5

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

Discloses read-only nature, dual source strategy (REST first, filesystem fallback), and that size/modified time are only available on fallback. No annotations provided, so description fully covers behavior.

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

Conciseness4/5

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

Three sentences effectively convey key information without redundancy. Could be slightly more streamlined, but structure is logical and front-loaded.

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

Completeness5/5

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

Completely explains behavior, fallback logic, limitations, and relationship to sibling tools. Adequate for a tool with no output schema and one parameter.

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?

Schema coverage is 100% with clear enum and description. Description adds context that omitting parameter lists all types, but this is minor addition beyond schema.

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 clearly states the tool lists model files grouped by type, and distinguishes it from sibling tools like search_models and download_model by specifying its use case.

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

Usage Guidelines5/5

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

Explicitly advises using this tool to check available models before generating or downloading, and contrasts with search_models (discover) and download_model (fetch).

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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