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SorataYang

Qiao-MCP

by SorataYang

add_effective_width

Add effective width to beam elements by defining I-end and J-end factors and Dz offsets, ensuring accurate section behavior in bridge models.

Instructions

    Add effective width to beam elements (添加截面有效宽度).

    Args:
        element_ids: Element ID(s) (单元编号)
        factor_i: I-end factor (I端系数)
        factor_j: J-end factor (J端系数)
        dz_i: I-end Dz offset (I端 Dz 偏移)
        dz_j: J-end Dz offset (J端 Dz 偏移)
        group_name: Boundary group name (边界组名)
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dz_iNo
dz_jNo
factor_iYes
factor_jYes
group_nameNo
element_idsYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.3.1

TDQS

B3.2/5.0
Behavior2/5

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

Annotations are all neutral false, so the description carries the full burden of behavioral disclosure. It never explains side effects, whether existing effective widths are overwritten, whether a boundary group must already exist, or what 'adding' does to the model beyond the literal action.

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 opening action sentence is concise and front-loaded, and the Args block is structured with no obvious fluff. The bilingual repetition slightly lengthens the text but remains informative.

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?

For a mutation tool with no annotations and no output schema, the description is thin on operational context. It covers parameter labels well but omits prerequisites, side effects, units, and the relationship between effective width and beam elements, leaving the agent to rely on assumptions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description compensates by explaining every parameter: element_ids, I/J factors, Dz offsets, and the boundary group. It adds meaning beyond the bare schema titles, such as 'I-end factor', 'J-end Dz offset', and 'boundary group name'.

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?

States a specific verb and resource ('Add effective width to beam elements'), making the core action and target clear. It does not explicitly differentiate itself from sibling add_* tools, but the resource name narrows the scope sufficiently.

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?

No guidance is given about when to use this tool versus alternatives. The sibling list contains many related section/update tools, but the description provides no criteria, prerequisites, or exclusions to help an agent select this tool.

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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