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SorataYang

Qiao-MCP

by SorataYang

add_shrink_function

Define a custom shrinkage function by specifying name, shrinkage strain over time, and scale factor for bridge structural analysis.

Instructions

    Add user-defined shrinkage function (添加自定义收缩函数).

    Args:
        name: Function name (函数名称)
        shrink_data: Shrinkage strain over time [[time(days), strain], ...]
                     (收缩应变表 [[天数, 应变], ...])
        scale_factor: Scale factor (比例系数)
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
shrink_dataNo
scale_factorNo

Schema Changelog

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

  1. First observedv0.3.1

TDQS

A3.6/5.0
Behavior2/5

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

Annotations provide no behavioral hints (all false), so the description must carry this burden. 'Add' implies mutation, but the description does not say what happens on name collision, whether shrink_data may be omitted, or how scale_factor affects the definition. There is no mention of return values or side effects beyond the add action itself.

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 definition is compact and front-loaded with a one-line purpose followed by a short arg list. Bilingual duplication lengthens it slightly but does not obscure the essential content.

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?

For a simple function-addition tool, parameter semantics are reasonably covered, but no output schema and no behavioral details leave gaps around overwrite/idempotency and optional inputs. It is adequate but not complete.

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 coverage is 0%, so the description must explain parameters, and it does. It documents name, gives a concrete data shape for shrink_data with units ([[time(days), strain], ...]), and defines scale_factor as a multiplier. Minor gap: it does not explain what scale_factor multiplies or the meaning of a null shrink_data.

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 opens with 'Add user-defined shrinkage function,' naming a specific verb and resource. This clearly distinguishes it from siblings like add_creep_function and add_spectrum_function, whose domain differs by material effect.

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?

Usage context is implied by the function name and 'user-defined shrinkage function' wording, but the description never states when this tool should be preferred over alternative function-definition tools, nor does it mention any exclusions or prerequisites.

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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