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/ai-use-case-intake

Intake a proposed AI use case and risk-classify it (EU AI Act tier / NIST AI RMF context), then gate it with the controls and documentation required before it can proceed. Use for AI governance intake, an AI use-case review board, or deciding what rigor a new AI project needs.

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awesome-claude-security
11111 skills17 agents13 commands1 MCP

Claude Code

$ npx -y skills add jassics/awesome-claude-security --skill ai-use-case-intake --agent claude-code

SKILL.md

ai-use-case-intake.SKILL.md
name: ai-use-case-intake
description: >-
  Intake a proposed AI use case and risk-classify it (EU AI Act tier / NIST AI RMF
  context), then gate it with the controls and documentation required before it can
  proceed. Use for AI governance intake, an AI use-case review board, or deciding
  what rigor a new AI project needs.

Goal

A governance decision record for a proposed AI use case: its risk classification, the obligations that follow, the required controls/evidence, and a clear proceed / proceed-with-conditions / do-not-proceed outcome.

Steps

1. **Capture the use case** — purpose, users and affected people, data used, autonomy/impact on decisions, deployment context, and vendor/build status. 2. **Classify risk:**

  • **EU AI Act tier** — unacceptable (prohibited) / high-risk / limited

(transparency) / minimal. High-risk and prohibited categories drive most obligations; check whether the use case falls in a listed high-risk area.

  • **NIST AI RMF context** — characterize impact, stakeholders, and harm

potential (reuse `ai-safety:harm-modeling`). 3. **Derive obligations** from the tier: required documentation (model/data cards, intended-use + limitations), human oversight, transparency/disclosure, data governance, testing/eval evidence, logging, and post-market monitoring. 4. **Map required controls to evidence** — which already exist vs. gaps. Pull from `ai-safety:safety-evaluation`, `bias-fairness-assessment`, `guardrail-review`, `responsible-ai-assessment`. 5. **Decide & record** — proceed / conditions / stop, with owner, conditions, and review date. Add to the AI inventory/register.

Output

An intake decision record: use case · risk tier · obligations · required controls · evidence status · decision · conditions · owner · review date. Use `security-reporting` for the record and an executive summary; this also feeds the org's AI inventory.

Notes

Classify the risk tier first — it sets how much rigor everything else needs, and it catches prohibited uses before effort is spent. Keep the register current; intake is the front door of the governance program, not a one-time form. Verify current EU AI Act / NIST AI RMF text and any sector rules.

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@jassics
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A Claude Code plugin marketplace for the full cybersecurity & GenAI-security lifecycle — from recon and threat modeling to detection engineering, GRC, and CISO-level strategy. A pentester knows which OWASP test bends a broken-access-control endpoint.

11111 skills17 agents1 MCP
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Questions about ai-use-case-intake.

Which coding agents can use ai-use-case-intake?
ai-use-case-intake installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.