Document type
Guidelines
Documents, 8
Every document of this type
Each with its area and its purpose; a document that states no purpose gets a line naming its type and area. A title in a corpus area opens the document's page, which holds the record and, where the document has them, its outline, frameworks, and related documents; a title in the Library area is a library specification with no page and opens its source on GitHub. The full text of every document is read on GitHub.
- Adversarial Evaluation Suite Development GuidelineAIThis guideline provides an organization-neutral method for developing adversarial evaluation suites for AI models and AI systems. It supports repeatable testing for misuse resistance, data leakage, prompt injection, unsafe tool use, robustness, and lifecycle assurance.
- AI Synthetic-Content Provenance GuidelineAIThis guideline provides implementation guidance for the AI-generated-content transparency obligations that ai/policy-ai-compliance.md Section 9.2 and the EU jurisdiction annex state at the policy and regulatory level. Those surfaces establish what must be labelled and when; this guideline is the how: the digital content transparency techniques an implementer selects and operates so that AI-generated or manipulated output is marked, detectable, and disclosed.
- Ethical AI Use GuidelineAIThis guideline provides practical direction for all staff, developers, and managers on the ethical use of AI tools and systems within the organization. It translates the organization's AI governance principles into concrete day-to-day expectations, helping employees understand their responsibilities when using, developing, or relying on AI.
- AI Coding Assistant Security GuidelineDev securityThis guideline defines requirements and best practices for the secure use of AI coding assistants, tools such as Claude Code, GitHub Copilot, Cursor, Windsurf, and equivalent products, within the software development lifecycle.
- ESG and AI Ethics Disclosure GuidelineGovernanceThis guideline defines the organization's approach to disclosing Environmental, Social, and Governance (ESG) performance and AI ethics commitments to external stakeholders. It provides direction on what to disclose, how to disclose it, and which standards and frameworks govern disclosure content.
- Minimum Viable Governance Structure GuidelineGovernanceThe library references multiple governance forums (AI Governance Council, Enterprise Risk Committee, Board Risk Committee, Architecture Review Board, Change Advisory Board, Data Council, Reliability Council, Capacity Council, and others). A small or mid-sized organization cannot staff all of these as discrete bodies. This guideline shows how an adopting organization can implement the library's governance content at three maturity tiers, consolidating forums where appropriate and naming clear seats for the responsibilities the library assigns.
- Emergency Response and Protective Actions GuidelineResilienceThis guideline provides organization-neutral guidance for immediate protective actions during emergencies that may affect personnel safety, facilities, operations, technology services, data, suppliers, or continuity response.
- Quantitative Risk Analysis GuidelineRiskThis guideline provides voluntary guidance for applying quantitative risk analysis techniques alongside the qualitative 5×5 matrix approach defined in risk/procedure-risk-assessment-methodology.md. Quantitative methods complement qualitative scoring by expressing risk in financial terms, supporting capital allocation decisions, cyber insurance sizing, and Board-level risk reporting.
With script, All Documents, filtered to Guidelines, lists these 8 documents, and the area chips holding any of them, and its text filter, narrow them further.