Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add CarbeneAI/Forge --skill nistairmfgit clone --depth 1 https://github.com/CarbeneAI/ForgeWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/carbeneai/forge/nistairmf)<a href="https://agentmods.dev/skills/carbeneai/forge/nistairmf"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/nistairmf/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/carbeneai/forge/nistairmf"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/nistairmf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00168 | $0.01527 |
| Opus 5 | $0.00084 | $0.00763 |
| Sonnet 5 | $0.00034 | $0.00305 |
| Haiku 4.5 | $0.00017 | $0.00153 |
Grade A, and why
nist-ai-rmf scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NIST AI Risk Management Framework (AI RMF 1.0) Skill
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 |
| 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 (e.g., MAP 1.5, MEASURE 2.3) — not just function names.
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 categories and subcategories
The AI RMF Playbook (companion document) provides suggested actions for each category and subcategory.
The Four Core Functions
GOVERN — Organizational Accountability (6 categories)
Sets the organizational culture, accountability, and risk tolerance for AI. GOVERN underpins all other functions.
| Category | Focus |
|---|---|
| GV-1 | AI risk management policies, processes, procedures and practices in place |
| GV-2 | Accountability structures for AI risk management |
| GV-3 | Organizational roles and responsibilities defined |
| GV-4 | Cross-functional team collaboration (AI, legal, privacy, security) |
| GV-5 | Organizational risk tolerance communicated and reflected in AI policies |
| GV-6 | Policies for AI risk aligned with applicable laws, regulations, principles |
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 136 lines · 168 tokens per session scan A 2b16f20cfb4a
nist-ai-rmf is a skill published in the GitHub repository CarbeneAI/Forge (9 stars, last pushed 1mo ago), licensed MIT. It adds 168 tokens to every session and 1,527 once invoked, about $0.0008 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
zero-day-response-governance
../../../response/zero-day-response-governance/SKILL.md.
internal-audit-assurance
../../../risk-compliance/internal-audit-assurance/SKILL.md.
ai-ethics-governance
../../../platform-ai/ai-ethics-governance/SKILL.md.
third-party-vendor-risk
../../../platform-ai/third-party-vendor-risk/SKILL.md.
compliance-mapping
../../../risk-compliance/compliance-mapping/SKILL.md.
privacy-dpia
../../../risk-compliance/privacy-dpia/SKILL.md.