Token导航 LogoToken导航

Agent Skill · AI 工具

msa(多发性硬化症)

msa 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

msa 是AI 工具类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证为 MIT,第三方扫描已通过,按安装量在AI 工具类的 2,536 个 Skill 里排第 1,873。

总安装 424周安装 17GitHub Stars 1下载 137核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:msa(多发性硬化症)
来源仓库:https://github.com/robdtaylor/personal-ai-infrastructure
仓库路径:skills/msa
安装命令:
npx skills add https://github.com/robdtaylor/personal-ai-infrastructure --skill Msa
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/robdtaylor/personal-ai-infrastructure --skill Msa

这个 Skill 是做什么的

AI 工具类 Skill 用来扩展助手本身的能力,例如接模型、接检索、接外部服务。

msa 用于处理 GitHub 仓库和协作信息。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。适合围绕仓库状态、Issue 和 Pull Request 进行整理。可通过 npx 命令安装并使用原始文档指导使用。

使用前应确认权限范围及是否会触发文件读写或网络请求。msa 属于AI 工具类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/msa

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/robdtaylor/personal-ai-infrastructure --skill…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

msa 怎么安装?

在终端执行 npx skills add https://github.com/robdtaylor/personal-ai-infrastructure --skill Msa。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

msa 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

msa 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

msa 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

msa 用的人多吗?

公开数据是累计安装 424 次,近一周安装 17 次,下载 137 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

msa 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理AI 工具类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

AI 工具类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
executing-plans

执行计划 · Codex、Claude

1,515,336173,110只读MIT通过
verification-before-completion

完成前的验证 · Codex、Claude

1,319,472173,121权限未标注MIT通过
subagent-driven-development

子 Agent 驱动开发 · Codex、Claude

1,312,416173,138只读MIT通过
copy-editing

复制编辑 · Codex、Claude

1,209,57625,632只读MIT通过
paywall-upgrade-cro

付费专区升级 cro · Codex、Claude

1,030,17625,617只读MIT通过
msa

多发性硬化症 · 本页

4241只读MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Measurement System Analysis (MSA)

When to Activate This Skill

  • "Conduct gage R&R study"
  • "Evaluate measurement system for [gage/characteristic]"
  • "Calculate %GR&R"
  • "Perform attribute agreement analysis"
  • "What's the ndc for this gage?"
  • "Is this measurement system acceptable?"
  • "MSA requirements for [characteristic]"

Purpose of MSA

MSA determines how much of the observed process variation is due to the measurement system rather than the actual process. Before making decisions based on measurement data, we must verify the measurement system is adequate.

Why MSA Matters

Without MSA:

  • "Good" parts may be rejected
  • "Bad" parts may be accepted
  • Process capability may be understated
  • SPC decisions may be wrong
  • Customer complaints may result

With MSA:

  • Measurement confidence established
  • Gage selection validated
  • Training effectiveness verified
  • Calibration adequacy confirmed

Types of MSA Studies

Variable MSA (Gage R&R)

For measurements that produce numerical data (dimensions, weight, temperature, etc.)

Study TypePurposeMethod
RepeatabilitySame operator, same gage, same part, multiple measurementsSingle operator, 10+ measurements
ReproducibilityDifferent operators, same gage, same partsMultiple operators measure same parts
Gage R&RCombined repeatability and reproducibilityStandard study
BiasDifference between measured and true valueCompare to master
LinearityBias across measurement rangeMultiple references
StabilityVariation over timeControl chart on master

Attribute MSA

For measurements that produce pass/fail, good/bad, or categorical results

Study TypePurposeMethod
Attribute AgreementOperator consistency and accuracyMultiple operators, multiple trials
KappaAgreement beyond chanceStatistical calculation
EffectivenessCorrect decisions vs. actual statusReference evaluation

Variable Gage R&R Study

Study Design (Standard AIAG)

ParameterMinimumPreferredNotes
Operators23Include typical operators
Parts510Represent process variation
Trials23Repeat measurements
Total readings2030-90More = better discrimination

Study Execution

  1. Select parts - Cover full range of process variation
  2. Number parts - Hidden from operator view
  3. Randomize - Operator doesn't know which part
  4. Measure - Each operator measures all parts, multiple trials
  5. Record - Document all measurements
  6. Analyze - Calculate %GR&R, ndc

Acceptance Criteria

MetricAcceptableMarginalUnacceptable
%GR&R (vs Process)<10%10-30%>30%
%GR&R (vs Tolerance)<10%10-30%>30%
ndc (Number of Distinct Categories)≥53-4<3

Interpretation

%GR&R <10%:

  • Measurement system acceptable
  • Can distinguish part-to-part variation
  • Suitable for SPC

%GR&R 10-30%:

  • May be acceptable for non-critical applications
  • Requires customer approval for critical characteristics
  • Consider improvement actions

%GR&R >30%:

  • Measurement system not acceptable
  • Must improve before use
  • Consider: different gage, training, environment

ndc (Number of Distinct Categories):

  • Represents the number of non-overlapping confidence intervals that span the product variation
  • ndc ≥5 required for variable data
  • ndc <5 means the measurement system cannot adequately distinguish part-to-part variation (acts more like attribute good/bad only)

Gage R&R Calculations

ANOVA Method (Preferred)

Analysis of Variance separates total variation into:

  • Part-to-part variation
  • Operator variation
  • Operator × Part interaction
  • Repeatability (equipment)
  • Reproducibility (operator)

Range Method (X-bar/R)

Simpler calculation, widely used:

Repeatability (EV) = R̄ × K₁
Where: R̄ = average range across all operators
       K₁ = factor based on number of trials

Reproducibility (AV) = √[(X̄diff × K₂)² - (EV²/nr)]
Where: X̄diff = range of operator averages
       K₂ = factor based on number of operators
       n = number of parts
       r = number of trials

GR&R = √(EV² + AV²)

%GR&R = (GR&R / TV) × 100
Where: TV = Total Variation = √(GR&R² + PV²)
       PV = Part Variation

ndc = 1.41 × (PV / GR&R)

Attribute Agreement Analysis

When to Use

  • Go/No-go gages
  • Visual inspection
  • Pass/fail tests
  • Any categorical decision

Study Design

ParameterMinimumPreferred
Appraisers23
Samples2030-50
Trials23
Sample mixInclude borderline50% good, 50% bad, include borderline

Key Metrics

MetricDescriptionTarget
Within Appraiser AgreementSelf-consistency≥90%
Between Appraiser AgreementAppraiser vs. Appraiser≥90%
Appraiser vs. StandardAppraiser vs. Reference≥90%
KappaAgreement beyond chance≥0.75

Kappa Interpretation

Kappa ValueInterpretation
<0.20Poor agreement
0.21-0.40Fair agreement
0.41-0.60Moderate agreement
0.61-0.80Substantial agreement
0.81-1.00Almost perfect agreement

Other MSA Studies

Bias Study

Measures systematic error (difference from true value)

Method:

  1. Obtain reference standard (known true value)
  2. Measure standard multiple times (≥10)
  3. Calculate average of measurements
  4. Bias = Average - Reference value

Acceptance: Bias ≈ 0 or within calibration tolerance

Linearity Study

Measures bias across the measurement range

Method:

  1. Select 5+ reference standards across range
  2. Measure each standard multiple times
  3. Plot bias vs. reference value
  4. Fit regression line

Acceptance: Linearity (slope × Process Variation) <5%

Stability Study

Measures variation over time

Method:

  1. Select stable reference part/standard
  2. Measure periodically (daily, weekly)
  3. Plot on control chart
  4. Monitor for trends or out-of-control

Acceptance: Stable control chart, no trends


MSA Requirements by Application

IATF 16949 Requirements (7.1.5.1.1)

  • MSA required for all measurement systems in Control Plan
  • Shall include study guidance and acceptance criteria
  • Alternative methods may be used with customer approval

Application Guidelines

CharacteristicRequired MSACriteria
Critical (CC)Gage R&R (variable) or Attribute Agreement%GR&R <10%
Significant (SC)Gage R&R (variable) or Attribute Agreement%GR&R <30%
StandardGage R&R recommended%GR&R <30%
SPC-monitoredGage R&R requiredndc ≥5

Common MSA Issues and Solutions

IssueLikely CauseSolution
High repeatabilityGage resolution, conditionBetter gage, calibrate, repair
High reproducibilityTraining, techniqueStandardize method, train
High interactionOperator-dependent methodSimplify method, fixture
Poor ndcGage can't see variationMore sensitive gage
Low KappaAmbiguous criteriaDefine clearer standards
BiasCalibration, wearRecalibrate, adjust

Output Format

When generating MSA content:

# MSA Study Report

## Study Information
| Field | Value |
|-------|-------|
| **Study Type** | Gage R&R / Attribute Agreement |
| **Gage ID** | [ID] |
| **Gage Description** | [Type, range, resolution] |
| **Characteristic** | [What is measured] |
| **Specification** | [Tolerance] |
| **Study Date** | [Date] |
| **Conducted By** | [Name] |

## Study Parameters
| Parameter | Value |
|-----------|-------|
| Operators | [Number and names] |
| Parts | [Number] |
| Trials | [Number] |
| Total measurements | [Count] |

## Results
| Metric | Value | Acceptance | Status |
|--------|-------|------------|--------|
| %GR&R | [X]% | <10% / <30% | PASS/FAIL |
| ndc | [X] | ≥5 | PASS/FAIL |
| Repeatability | [X]% | - | - |
| Reproducibility | [X]% | - | - |

## Conclusion
[ACCEPTABLE / MARGINAL / UNACCEPTABLE]

## Actions (if required)
- [Action items]

Integration with Related Skills

ControlPlan

All gages in Control Plan require MSA:

  • Variable gages: Gage R&R
  • Attribute gages: Attribute agreement
  • MSA status verified before production

Load: read ~/.claude/skills/Controlplan/SKILL.md

SPC

SPC validity depends on MSA:

  • ndc ≥5 required for variable SPC
  • Measurement variation affects control limits
  • Poor MSA = poor SPC decisions

Load: read ~/.claude/skills/Spc/SKILL.md

AutomotiveManufacturing

MSA supports work instruction development:

  • Measurement methods documented
  • Gage identification required
  • Operator training verified

Load: read ~/.claude/skills/Automotivemanufacturing/SKILL.md


Supplementary Resources

For detailed guidance: read ~/.claude/skills/Msa/CLAUDE.md

For study templates: ls ~/.claude/skills/Msa/templates/

For acceptance criteria: read ~/.claude/skills/Msa/reference/acceptance-criteria.md

For calculation formulas: read ~/.claude/skills/Msa/reference/calculation-formulas.md

平台分布

Claude Code

28.98%
按下载量换算40

windsurf

22.33%
按下载量换算31

trae

18.87%
按下载量换算26

OpenCode

12.02%
按下载量换算16

Cursor

8.15%
按下载量换算11

Codex

3.86%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

继续浏览同类 Skills