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mayjack0312
by mayjack0312

eda_lib_simulation_model_search

Search simulation models in the library by keyword, classification, or model type to retrieve matching model properties for your design needs.

Instructions

lib_SimulationModel.search(key: string, libraryUuid?: string, classification?: Array, simulationModelType?: ELIB_SimulationModelType, itemsOfPage?: number, page?: number) -> Promise<Array> 搜索仿真模型 remarks: ADD since EDA v3.2.167 returns: 搜索到的仿真模型属性列表

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argsNo按官方签名顺序排列的JSON参数数组
windowIdNo目标EDA窗口ID;省略时使用当前活动窗口

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

B3/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral disclosure burden. It communicates that the tool returns a list, but does not explicitly state that it is read-only, describe pagination behavior, matching semantics, permission requirements, or any side effects. For a search tool with no annotation coverage, this is a notable transparency gap.

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 description is compact and efficient, combining the signature, a one-line Chinese summary, version remark, and return description without filler. The essential information is front-loaded in the signature line, though the Chinese description is somewhat redundant with the signature.

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?

Given a six-parameter search function with no annotations and no output schema, the description is incomplete. It lacks explanation of each parameter's meaning, enum values for `simulationModelType`, default pagination behavior, result item structure, and usage examples, leaving an agent with only names and types to infer correct invocation.

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 description adds substantial value beyond the generic `args`/`windowId` schema by enumerating the actual signature: `key`, `libraryUuid`, `classification`, `simulationModelType`, `itemsOfPage`, and `page` with types and ordering. This compensates for the schema's lack of the real parameters, though it still omits detailed semantics and allowed enum values.

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 states a clear action ('搜索仿真模型' / search simulation models) on a specific resource, backed by the full signature `lib_SimulationModel.search(...)`. It identifies the result as an array of simulation model search items, which makes the tool's purpose understandable. However, it does not explicitly distinguish itself from the sibling `eda_lib_simulation_model_get`, so it stops short of full sibling differentiation.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as `eda_lib_simulation_model_get` or other library search tools. The description only restates the search action and signature without specifying conditions, exclusions, or preferred scenarios.

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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