compliance-os
Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario libr
Profile →npx skills add alirezarezvani/claude-skills --skill compliance-os --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Compliance OS — Meta-Orchestrator Multi-framework compliance program orchestration. **Four decisions, no per-framework deep-dive:** 1. **Which frameworks apply to this company?** — `framework_selector.py` ranks the 12 supported frameworks against a company profile (industry, geography, AI use, medical, financial, headcount, customers, healthcare-PHI, NIS2 essential/important entity, US gov contractor) and returns applicable ones with dependency graph 2. **How much do selected frameworks overlap?** — `cross_framework_mapper.py` computes control-level overlap with confidence rating; outputs unified control matrix + evidence-reuse opportunities 3. **What does a mock audit produce?** — `audit_simulator.py` generates 8–15 finding scenarios with severity distribution matching IIA expectations + interview questions per control 4. **What's the unified evidence checklist?** — `evidence_pool_generator.py` consolidates evidence across enabled frameworks; outputs which artefact satisfies which controls across which frameworks This skill is **NOT** a per-framework deep-dive. The per-framework skills (`ra-qm-team/skills/iso42001-specialist/`, `compliance-team-eu-ai-act/`, `ra-qm-team/skills/gd
- Keywords
- Quick Start
- Key Questions (ask these first)
- Core Responsibilities
- 1. Framework Selection
- 2. Cross-Framework Control Mapping
- 3. Audit Simulation
- 4. Evidence Pool
- Workflows
- Workflow 1: Program Bootstrap (multi-framework, 4–8 weeks)
- Workflow 2: Annual Audit Calendar (yearly)
- Workflow 3: Pre-Certification Readiness (per new framework, 6–12 weeks)
- Workflow 4: Evidence Pool Consolidation (quarterly)
- Output Standards
Decision A: Which frameworks apply for the company? python scripts/framework_selector.py # embedded mid-stage AI SaaS sample python scripts/framework_selector.py path/to/profile.json Decision B: Compute cross-framework overlap python scripts/cross_framework_mapper.py # embedded ISO 27001 + SOC 2 sample python scripts/cross_framework_mapper.py path/to/control_libs.json Decision C: Simulate an audit python scripts/audit_simulator.py # embedded ISO 27001 sample python scripts/audit_simulator.py path/to/audit_scope.json Decision D: Consolidate evidence checklist across frameworks
What does the compliance-os skill do?
Compliance OS — meta-orchestrator that lets compliance teams CONFIGURE which frameworks apply, COMPUTE cross-framework control overlap, SIMULATE internal audits, and CONSOLIDATE evidence across multiple frameworks. Four decisions: (1) Given a company profile, which of the 12 supported frameworks apply (ISO 27001/13485/42001/14971, EU AI Act, MDR 745, GDPR, SOC 2, FDA QSR, NIST CSF 2.0, NIS2, HIPAA)? (2) Across selected frameworks, which controls overlap and how much evidence reuses? (3) For a given framework + scope, what does a realistic mock audit produce — drawing from the 205-scenario libr
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill compliance-os --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.