sentinel-stack

AI risk classification and governance skill. Classifies AI use cases by EU AI Act risk tier (Unacceptable/High/Limited/Minimal), enforces organizational AI acceptable use policies, determines transparency and human oversight requirements, tracks data lineage for AI-assisted outputs, and generates compliance artifacts for model governance. Use when evaluating AI use cases, building AI workflows, or assessing regulatory compliance.

Compliance audit log generator. Creates structured, immutable audit records (JSON-lines format) for guardrail decisions, DLP scans, 4-eyes review workflows, and AI-assisted outputs in regulated categories. Designed for SIEM and GRC platform ingestion with built-in retention governance per GDPR, SOC 2, and HIPAA. Use when you need audit logs, compliance trails, or interaction history.

Token-efficient communication mode. Compresses conversational prose (~65-75% output token savings) while keeping code, commands, and compliance artifacts untouched at full fidelity. Use when the user asks for "caveman mode", "brief mode", "less tokens", or when long sessions risk context pressure. Adapted from github.com/JuliusBrussee/caveman with sentinel-stack governance carve-outs.

Compliance artifact generator. Auto-generates audit evidence from guardrail detections, 4-eyes review gates, and DLP scans. Maps control evidence to SOC 2 Type II, ISO 27001, NIST CSF, and GDPR Article 30. Generates evidence packages on demand for auditors and tracks control effectiveness over time. Use for audit preparation, compliance evidence collection, or SOC 2/ISO 27001 artifact generation.

Governance decision validation skill. Reviews decisions for logical consistency, evidence quality, bias indicators, and completeness. Checks that decisions reference appropriate policies and have proper authorization. Outputs audit findings with severity ratings. Use for quality assurance of governance decisions or investigating concerns.