跳到正文
cccskills
免费在 GitHub 公开

rai-standards

Consolidated Responsible AI standards reference: NIST AI RMF 1.0, AI STRIDE threat-modeling overlay, EU AI Act risk tiers, and an open-standards catalog with phase mapping

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(7)

  • SKILL.md6.0 KB
  • references/ai-stride-overlay.md2.3 KB
  • references/eu-ai-act.md1.9 KB
  • references/nist-ai-rmf-govern.md2.3 KB
  • references/nist-ai-rmf-manage.md1.9 KB
  • references/nist-ai-rmf-map.md2.0 KB
  • references/nist-ai-rmf-measure.md2.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

RAI Standards Skill

This skill is the reusable standards package for the RAI Planner. It consolidates the embedded NIST AI RMF content, the AI STRIDE threat-modeling overlay, and a paraphrased EU AI Act reference so the phase playbook can stay focused on workflow and orchestration.

Attribution and licensing posture

  • NIST AI RMF 1.0 is a U.S. Government document and is reproduced here as public-domain reference material with attribution. Public-domain material carries no license obligation, so it adds no term to the package license expression.
  • EU AI Act content in this skill is paraphrased and attributed rather than quoted verbatim, consistent with the open legal-text posture used in the repository. The paraphrase is this repository's own expression.
  • The AI STRIDE overlay is Microsoft-authored reference material for threat-modeling reuse in the RAI workflow.

Every file in this package is therefore governed by the repository-original license. The table records the source each file draws on.

PathLicenseOrigin
references/nist-ai-rmf-govern.mdCC-BY-4.0Adapted from NIST AI RMF 1.0 (public domain)
references/nist-ai-rmf-map.mdCC-BY-4.0Adapted from NIST AI RMF 1.0 (public domain)
references/nist-ai-rmf-measure.mdCC-BY-4.0Adapted from NIST AI RMF 1.0 (public domain)
references/nist-ai-rmf-manage.mdCC-BY-4.0Adapted from NIST AI RMF 1.0 (public domain)
references/eu-ai-act.mdCC-BY-4.0Paraphrase of EU AI Act 2024/1689, not reproduced
references/ai-stride-overlay.mdCC-BY-4.0Repository-original
SKILL.md and remaining package contentCC-BY-4.0Repository-original

Framework index

NIST AI RMF trustworthiness characteristics

KeyCharacteristicDescription
validReliableValid and ReliableBase characteristic for correctness, robustness, and stability
safeSafeSafety and harm prevention under normal and adversarial conditions
secureResilientSecure and ResilientResistance to attack, misuse, and failure
accountableTransparentAccountable and TransparentGovernance, auditability, and decision provenance
explainableInterpretableExplainable and InterpretableUnderstandability of model behavior and outputs
privacyEnhancedPrivacy-EnhancedProtection of personal data and confidentiality
fairBiasManagedFair with Harmful Bias ManagedBias detection, mitigation, and equitable outcomes

Phase-to-framework mapping

RAI phasePrimary standards packageNotes
Phase 1 ScopingNIST AI RMF Govern + MapContext, purpose, stakeholders, and policy framing
Phase 2 Risk ClassificationNIST AI RMF GovernGovernance culture, DEI&A, and stakeholder engagement
Phase 3 Standards MappingNIST AI RMF Govern + MeasureCore standards mapping and TEVV alignment
Phase 4 Security Model AnalysisAI STRIDE overlay + MeasureThreat modeling and overlap with security analysis
Phase 5 Impact AssessmentNIST AI RMF ManageRisk prioritization, mitigation, and monitoring
Phase 6 Review and HandoffNIST AI RMF Manage + EU AI ActRegulatory review, incident response, and evidence handoff

Customer extension pattern

The default framework remains NIST AI RMF 1.0. When a customer supplies an additional framework, preserve the default NIST mapping as a baseline and layer the custom framework on top with explicit attribution. This keeps the planner interoperable while allowing organizations to add ISO, sector, or regional references without rewriting the core playbook.

Open-standards catalog

Use the links below as the reference catalog for open standards and governance resources. Do not reproduce normative text verbatim when the license posture does not allow it.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Consolidated accessibility skill entrypoint for WCAG 2.2, ARIA Authoring Practices, cognitive accessibility, Section 508, EN 301 549, design intent verification, and the Accessibility Planner workflow.

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

Build, refresh, report, or probe an accessibility coverage matrix across criteria, surfaces, and evidence methods. Use when assessing coverage with the accessibility runtime harness and generated evidence bundle.

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

Authoring skill for Architecture Decision Records (ADRs) supporting capture, from-planner-handoff, and adopt-template entry modes with selectable Y-Statement or MADR v4.0.0 output templates, supersession lineage, and ASR trigger evaluation.

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

Authoring conventions for exploratory data analysis notebooks and analytical dashboards, covering section sequence, visualization selection, scale thresholds, caching and state, and dashboard validation budgets. Use when composing or reviewing an EDA notebook, an analytical dashboard, or a dashboard test pass.

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

Architecture diagram authoring for cloud infrastructure and declared data catalogs. Use when rendering Azure IaC or DS_CATALOG_V1 relationships as caller-selected ASCII or Mermaid diagrams.

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

Create a durable Architecture Review Record from a confirmed System Architecture Reviewer scope, evidence, pillar analysis, trade-offs, and dispositions

中文简介正在准备中。当前显示原文说明。

microsoft/hve-core15322026年10月18日 更新

查看 microsoft 的全部技能

报告此技能的问题