academic-research-comp…
Guide a research project through the full academic lifecycle — from raw idea to concrete research question, literature grounding, methodology, writing,…
NIST AI 100-1 (AI RMF 1.0) expert. Stub-depth framework plugin that routes to the SCF crosswalk. Level up by adding framework-specific context, assessment workflow, and evidence patterns.
$ npx -y skills add GRCEngClub/claude-grc-engineering --skill nist-ai-rmf-expert --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/nist-ai-rmf-expertContext preview
The summary Claude sees to decide when to auto-load this skill.
NIST AI 100-1 (AI RMF 1.0) expert. Stub-depth framework plugin that routes to the SCF crosswalk. Level up by adding framework-specific context, assessment workflow, and evidence patterns.
name: nist-ai-rmf-expert description: NIST AI 100-1 (AI RMF 1.0) expert. Stub-depth framework plugin that routes to the SCF crosswalk. Level up by adding framework-specific context, assessment workflow, and evidence patterns. allowed-tools: Read, Glob, Grep
Stub-depth expertise for **NIST AI 100-1 (AI RMF 1.0)**. This plugin is scaffolded from the SCF crosswalk (158 SCF controls map to 91 framework controls) and defers to `/grc-engineer:gap-assessment` for the actual compliance check.
AI RMF is an **outcomes framework**, not a control catalog and not a certification. It organizes outcomes as Function → Category → Subcategory across four functions — **GOVERN**, **MAP**, **MEASURE**, **MANAGE** — applied across the AI system lifecycle. Subcategories describe desired risk-management outcomes; they do not prescribe specific controls. Concrete controls come from the SCF crosswalk: 158 SCF controls map to 91 AI RMF subcategories, referenced by subcategory ID (e.g. `GOVERN 1.1`, `MAP 2.3`), never by paraphrased prose.
Common failure modes when working with this framework: treating AI RMF as a control catalog to "implement", confusing the four functions with maturity levels, and mapping to subcategory prose instead of subcategory IDs.
TODO: replace with framework-specific overview. Minimum sections for Reference-depth upgrade:
All commands in this plugin route through `/grc-engineer:gap-assessment` with framework ID `general-nist-100-1-ai-rmf`. Reference-depth plugins add:
Full-depth plugins add framework-specific workflow commands (examples in sibling plugins like `soc2`, `fedramp-rev5`, `pci-dss`).
See the [Framework Plugin Guide](../../../../../docs/FRAMEWORK-PLUGIN-GUIDE.md) for the Stub → Reference → Full progression checklist.
Open-source GRC Engineering resource for Claude. claude-grc-engineering turns technical evidence from cloud, SaaS, code, and security tools into framework-aligned findings, gap reports, remediation guidance, evidence packages, and OSCAL workflows.
Repo: GRCEngClub/claude-grc-engineering
Guide a research project through the full academic lifecycle — from raw idea to concrete research question, literature grounding, methodology, writing,…
Expertise in evaluating AWS accounts for compliance — what checks are meaningful, which SCF controls they map to, and how to interpret aws CLI output.
Use when interpreting AWS Secrets Manager connector output, deciding between inspector and retrieve modes, drafting SCF-mapped controls for rotation / KMS /…
Expertise in evaluating Azure subscription findings from azure-inspector and mapping them to SCF controls.
Interpret CrowdStrike Falcon findings for sensor coverage, policy visibility, and host group scoping.
Interpret datadog-inspector findings and translate Datadog monitoring, audit, log-retention, SSO, and RBAC results into GRC evidence and remediation.