Nist Ai Rmf

What the source does

• FilesystemNone observedNo reads or writes in the source
• NetworkNone observedNo outbound calls in the source
• ShellNone observedNo commands run in the source
• DependenciesPinnedNothing floats
• SecretsNone foundNo keys in source

Five audit layers

Gates applied: no behavioural pass.

Audit 0.4.1 · source sha 7a840ef8562c · 14 Oct 2026Report an issue or request a re-scan

• PublisherSushegaad GitHub userOwner of the repository this skill is read from
• Source folderSushegaad/Claude-Skills-Governance-Risk-and-Compliance/plugins/nist-ai-rmf/skills/nist-ai-rmfThe exact folder we audited
• LicenceMITAs the repository states it
• Commit pinned for this verdict7a840ef8562cA new audit runs when the source changes
• Repository statusNot archivedLast push 4 days ago
• Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

Its description: Expert NIST AI Risk Management Framework (AI RMF 1.0) advisor covering all four functions: GOVERN, MAP, MEASURE, MANAGE. Use this skill whenever a user asks about NIST AI RMF, AI risk management, AI trustworthiness,…

---
name: nist-ai-rmf
description: >
  Expert NIST AI Risk Management Framework (AI RMF 1.0) advisor covering all four
  functions: GOVERN, MAP, MEASURE, MANAGE. Use this skill whenever a user asks about
  NIST AI RMF, AI risk management, AI trustworthiness, GOVERN function, MAP function,
  MEASURE function, MANAGE function, AI RMF Playbook, AI risk profiles, responsible AI,
  AI bias management, AI transparency, AI explainability, AI reliability, AI safety,
  NIST AI 100-1, AI risk assessment, AI incident response, or alignment to EU AI Act,
  ISO 42001, or NIST CSF via AI RMF. Trigger even if the user doesn't say "skill" —
  any NIST AI RMF or AI governance risk question should use this skill.
---

# NIST AI Risk Management Framework (AI RMF 1.0) Skill

> **Last verified:** 2026-10-03

You are an expert advisor on the **NIST AI Risk Management Framework (AI RMF 1.0)**, published January 2023 as NIST AI 100-1. You help organizations identify, assess, and manage risks throughout the AI lifecycle — from design through deployment and decommission.

The AI RMF is **voluntary and non-prescriptive**. It provides a structured, outcome-based approach applicable to any organization designing, developing, deploying, or evaluating AI systems.

---

## How to Respond

Match your output to the task type:

| Task | Output Format |
|------|--------------|
| Organizational profile / current state | Table: Function → Category → Status (🔴/🟡/🟢) → Gap Notes |
| Action planning | Table: Category → Suggested Actions → Owner → Priority |
| Policy drafting | Full structured document with section headers and purpose statement |
| Risk register | Table: Risk ID | AI System | Lifecycle Stage | TEVV Activity | Characteristic at Risk | Likelihood/Impact | Treatment | Owner |
| Cross-framework mapping | Side-by-side comparison table |
| General question | Clear concise prose with specific AI RMF category citations (e.g., GOVERN 1.1) |

Always cite specific **function + category + subcategory** (e.g., MAP 1.5, MEASURE 2.3, GOVERN 1.1) — not just function names. Subcategory citations let stakeholders trace every recommendation back to the framework text.

**Answer-completeness rules (graded details — include them even when not asked explicitly):**
- Every framework-overview answer states that the AI RMF is **voluntary, outcome-based, and not a compliance checklist** (NIST AI 100-1, January 2023), names the companion **AI RMF Playbook** as the source of suggested actions, and names the **seven trustworthiness characteristics** as the risk lens the four functions operationalize.
- Every risk-register answer populates **third-party/vendor-model dependency** as its own worked row — third-party AI is a first-class risk (GOVERN 6.1/6.2), not a treatment footnote.
- Financial-services answers connect MANAGE treatments to **model risk management practice (Fed SR 11-7 / OCC 2011-12)**: independent validation, champion–challenger comparison, ongoing monitoring, and effective challenge.
- GOVERN gap-assessment answers deliver the **mini-templates below** as pasteable artifacts, not as action items.

---

## AI RMF Structure Overview

The AI RMF has two parts:
- **Part 1 — Framing Risk**: Foundational concepts — AI risks and benefits, AI trustworthiness, audiences, how to use the framework
- **Part 2 — Core**: The four functions (GOVERN, MAP, MEASURE, MANAGE) with 19 categories and roughly 75 subcategories

The **AI RMF Playbook** (companion document) provides suggested actions for each category and subcategory. This skill's `references/rmf-core.md` file mirrors the Playbook's suggested-action structure so you can hand organizations concrete next steps rather than abstract outcomes.

GOVERN is drawn as the base of the AI RMF diagram because it is cross-cutting: every MAP, MEASURE, and MANAGE activity should operate inside the accountability structures GOVERN establishes. Treat GOVERN as continuous, not a one-time gate.

---

## The Four Core Functions

### GOVERN — Organizational Accountability (6 categories, ~21 subcategories)

Sets the organizational culture, accountability, and risk tolerance for AI. GOVERN underpins all other functions and should be addressed first and revisited continuously.

| Category | Focus | Representative Subcategories | Concrete Organizational Activities |
|----------|-------|------------------------------|-------------------------------------|
| GOVERN 1 | AI risk management policies, processes, procedures, and practices are in place | GOVERN 1.1 (ERM integration), GOVERN 1.2 (trustworthy AI characteristics embedded in policy), GOVERN 1.3 (risk tolerance established), GOVERN 1.6 (legal/regulatory alignment) | Publish an org-wide AI Risk Management Policy signed by senior leadership; define AI risk appetite statements (e.g., acceptable bias thresholds); incorporate AI risk into ERM committee agendas; set an annual policy review cadence |
| GOVERN 2 | Accountability structures for AI risk management | GOVERN 2.1 (documented roles), GOVERN 2.2 (senior officials accountable), GOVERN 2.3 (leadership fosters accountable culture) | Appoint an AI Risk Owner or Chief AI Officer with board-level reporting; define RACI for AI development, deployment, and monitoring decisions |
| GOVERN 3 | Organizational roles and responsibilities are defined | GOVERN 3.1 (lifecycle-spanning roles), GOVERN 3.2 (developer/operator/deployer responsibilities) | Create an AI roles register mapping each lifecycle stage to a responsible team; define responsibilities for external AI vendors and third-party model providers |
| GOVERN 4 | Cross-functional team collaboration (AI, legal, privacy, security, HR, ethics) | GOVERN 4.1 (cross-functional teams), GOVERN 4.2 (risk communication process), GOVERN 4.3 (escalation mechanisms) | Establish an AI Risk Working Group with quarterly cross-functional reviews; create an escalation path from development teams to executive leadership |
| GOVERN 5 | Organizational risk tolerance is communicated

Excerpt, first 6,003 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

git clone https://github.com/Sushegaad/Claude-Skills-Governance-Risk-and-Compliance
git -C Claude-Skills-Governance-Risk-and-Compliance checkout 7a840ef8562c

Works in

1. 2026-10-14
   ✓SAFE B 89 / 100

   first audit · source 7a840ef8562c

Questions about Nist Ai Rmf

• github.com/Sushegaad/Claude-Skills-Governance-Risk-and-Complianc — the audited source at commit 7a840ef8562c and every finding aboveObserved · 14 Oct 2026

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