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Ka1y0
by Ka1y0

Load an LM Studio model

lmstudio_load_model

Validate a downloaded model and context, then load it in LM Studio via lms load, without downloading.

Instructions

MUTATING and disabled by default. Validates a downloaded model and context before invoking lms load; never downloads.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
identifierNo
estimate_onlyNo
context_lengthNo
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the mutating nature, disabled-by-default status, validation behavior, and that it never downloads. This is strong behavioral disclosure, though it does not detail all side effects or error paths.

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?

A single, information-dense sentence. The key warnings are front-loaded, and every clause adds value. No wasted words.

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

Completeness2/5

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

The description covers core behavior but lacks parameter semantics, usage alternatives, and any description of return values or failure modes. Given the mutating nature and four parameters, this is insufficient for an agent to invoke it correctly without additional inference.

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 coverage is 0% and the description provides no explanation of the four parameters (model, identifier, estimate_only, context_length). The description's action context does not compensate for this gap, leaving the agent without guidance on what each parameter means or how to use them.

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 loads a model via 'lms load' after validation, and the title reinforces the resource. It distinguishes from siblings like unload/list by focusing on the loading action. The MUTATING and disabled-by-default prefix adds specificity.

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 use for loading validated models and warns it is disabled by default, but it does not explicitly state when to use this over alternatives or when not to use it. No alternative tools are named, and the 'disabled by default' is more a caution than a usage guideline.

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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