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lib_set_model_name

Set a SchLib symbol’s footprint model reference by rewriting the ModelName for a selected component implementation, optionally targeting the current or a named model.

Instructions

Set a model's model_name (footprint reference) on a SchLib symbol.

Rewrites the ModelName of one of the component's implementations. If model_name is given, the model whose current ModelName matches is targeted; otherwise the current (or first) model is used.

Args: component_name: the component's LibReference. new_model_name: the new model_name to write. model_name: optional current model_name to target a specific one. library_path: optional .SchLib path; defaults to the focused lib.

Returns: {"success": true, "component": "...", "new_model_name": "..."}.

Input Schema

NameRequiredDescriptionDefault
model_nameNo
library_pathNo
component_nameYes
new_model_nameYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.1

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that this is a rewrite operation, explains targeting behavior, the default focused library, and the success return shape. It does not state required permissions, whether changes are saved automatically, or what happens if no matching model exists, leaving important mutation behavior unstated.

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?

The purpose is front-loaded in the first sentence, followed by targeted behavioral notes and an Args/Returns structure. There is some redundancy between the opening sentence and the second sentence, and the Args section partly repeats schema names, but the extra detail is justified by zero schema description coverage.

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

Completeness3/5

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

The description covers the main operation, all parameters, default library behavior, and return shape, which is adequate for a four-parameter mutation tool with an output schema. Because there are no annotations, the description should more fully carry safety and failure-mode context. Missing prerequisites and save/commit behavior leave it only minimally complete for a mutating library operation.

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 description coverage is 0%, so the description must define the parameters, and it documents all four. It clarifies component_name as the LibReference, distinguishes new_model_name from the optional current model_name used for targeting, and explains library_path defaulting to the focused library. It could add still more detail, such as expected path format, but it compensates well for the empty schema.

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 gives a specific verb and resource: setting a SchLib symbol model's ModelName / footprint reference. It also identifies the affected object as one of the component's implementations. It does not explicitly distinguish itself from related siblings such as lib_set_model_source or lib_remove_model, so it falls short of a 5.

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 explains how model_name selects a specific existing model versus falling back to the current or first model. That is useful operational guidance. However, it gives no explicit when-to-use versus alternatives or prerequisites for choosing this tool over model-source or model-removal siblings.

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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