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Aql Sampling Plan

aql_sampling_plan

按 ISO 2859-1(一般检验水平 II·正常检验·单次抽样)计算 AQL 抽样计划。

输入整批数量 lot_size 与 AQL 值(支持 1.0 / 2.5 / 4.0),返回样本量、接受/拒收 判定值(Ac/Re)与按缺陷等级(致命/主要/次要)的常用 AQL 组合建议。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aqlNoAQL 值,可选 1.0 / 2.5 / 4.0(默认 2.5,即主要缺陷的常用值)。
lot_sizeYes整批数量(单位:件/pcs)。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

No annotations are provided, so the description carries the disclosure burden. It discloses key behavioral constraints: the exact standard and variant (GIL II, normal, single sampling), the supported AQL values (1.0/2.5/4.0), and the kinds of results returned. It does not mention handling of unsupported AQL values or extreme lot sizes, but this is a minor gap for a calculation tool.

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?

The description is two tight sentences with the standard and core function front-loaded. Every clause carries information: standard, inspection level, sampling type, inputs, supported AQL values, and outputs. No filler.

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

Completeness5/5

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

For a deterministic calculation tool with an output schema, the description fully covers the standard, inputs, supported values, and result contents. An agent can decide to invoke it and knows what to expect without needing additional context.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already fully documents lot_size and aql, including the default and allowed values. The description mostly restates this same information and adds no deeper parameter semantics beyond what the schema provides.

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 a specific verb+resource: it computes an AQL sampling plan per ISO 2859-1, with concrete inputs (lot_size, AQL) and outputs (sample size, Ac/Re, defect-class suggestions). It is immediately distinguishable from the sibling audit/checklist and supplier-scorecard tools.

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

Usage Guidelines4/5

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

The description gives clear context: use this when you need an ISO 2859-1 single-sampling plan at General Inspection Level II with normal inspection. It does not explicitly name alternatives or exclusions, but the sibling tools are unrelated domains, so the intended usage is evident.

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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