ai-agent-compliance-controls

name	ai-agent-compliance-controls
description	Use when mapping AI agent operations to SOC 2, ISO 27001, HIPAA, audit logs, control testing, attestations, and compliance evidence.
metadata	{"portable":true,"compatible_with":["claude-code","codex"]}

AI Agent Compliance Controls

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, [phone].

Use When

• Design compliance controls for agent actions, logs, approvals, evidence, and access boundaries.
• Map agent operations to SOC 2, ISO 27001, HIPAA, or control testing requirements.
• Prepare control evidence and audit-ready narratives for agentic AI systems.

Do Not Use When

• The work is not AI-specific or agentic-AI-specific.
• A narrower retained AI parent skill fits the request better.

Required Inputs

• Product, tenant, user, data, risk, and operational context relevant to the AI workflow.
• Target artifact: design, implementation plan, audit, test strategy, UX flow, commercial policy, or runbook.
• Constraints from security, privacy, reliability, billing, support, and compliance stakeholders when relevant.

Workflow

1. Read this SKILL.md first.
2. Load references/routing.md to select the absorbed child reference that matches the task.
3. Load only the selected child reference files needed for the current request.
4. Produce execution-oriented output with assumptions, risks, evidence, and next actions where relevant.

Quality Standards

• Keep routing explicit: name which reference files were used when the work depends on absorbed material.
• Preserve tenant isolation, auditability, cost controls, safety gates, and operational evidence when they matter.
• Prefer concrete contracts, checklists, tables, schemas, runbooks, and decision records over broad summaries.

Anti-Patterns

• Loading every absorbed reference by default.
• Treating AI-specific billing, compliance, safety, or UX concerns as generic SaaS work without checking AI failure modes.
• Hiding retired skill names; old slugs must remain discoverable through references/routing.md.

Outputs

• A concrete deliverable matched to the request: architecture, implementation plan, audit, policy, runbook, UX flow, test strategy, or operating model.
• The selected consolidated reference files and any assumptions, risks, evidence requirements, or follow-up actions that affect execution.

References

• references/routing.md maps retired child skill slugs to their consolidated reference folders.

Consolidated Child References

• Load references/routing.md to map retired AI child skill slugs to their reference modules.