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
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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
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compliance-os.SKILL.md
---name: "compliance-os"
description: "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 library? (4) Across selected frameworks, what's the unified evidence checklist with reuse map? Use when standing up a multi-framework program, planning the annual audit calendar, or preparing for certification stage 1. Does NOT replace per-framework skills (it orchestrates them)."
license: MIT
metadata:
version: 1.0.0
author: Alireza Rezvani
category: compliance-os
domain: multi-framework-compliance-orchestration
updated: 2026-05-13
python-tools: framework_selector.py, cross_framework_mapper.py, audit_simulator.py, evidence_pool_generator.py
frameworks: iso-27001, iso-13485, iso-42001, iso-14971, eu-ai-act, eu-mdr-745, gdpr, soc-2, fda-qsr, nist-csf, nis2, hipaa
---# 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/gdpr-dsgvo-expert/`, etc.) do the operational work. Compliance OS orchestrates them.
This skill is **NOT** a substitute for binding legal advice. Cross-framework mappings reflect published guidance (ISO standards, regulations, EDPB/Commission guidance, IIA / AICPA professional standards). Novel cross-walks should be reviewed with counsel.
## Keywords
compliance orchestration, multi-framework compliance, compliance OS, cross-framework mapping, control overlap, evidence pool, evidence reuse, audit simulation, mock audit, internal audit programme, GRC, governance risk compliance, framework selector, compliance program, integrated compliance, ISO 19011, IIA IPPF, AICPA AT-C, NIST CSF profile, multi-cert program, SOC 2 + ISO 27001, ISO 27001 + ISO 42001, ISO 13485 + MDR 745, AI Act + ISO 42001, GDPR + ISO 27001, compliance officer, compliance team workflow, certification readiness
## Quick Start
```bash
# Decision A: Which frameworks apply for the company?
python scripts/framework_selector.py # embedded mid-stage AI SaaS sample
- **Have you named every applicable framework?** Forgetting one means rebuilding the audit program later. Run `framework_selector.py` with your profile.
- **What's the most certificate / regulation your company already operates?** That's your reuse anchor. Map every new framework against it.
- **What's the audit calendar?** A multi-framework program means surveillance audits stacked through the year — plan auditor independence + capacity.
- **Where is evidence stored?** Multi-framework programs collapse when evidence lives in one team's drive without an index. Run `evidence_pool_generator.py` to surface the reuse opportunities.
- **What's the management-review cadence across frameworks?** Each framework wants its own management review, but a single integrated review (per ISO Annex SL) typically satisfies all of them with one calendar slot.
- **Who owns the meta-program?** If no single accountable role, the program fragments.
## Core Responsibilities
### 1. Framework Selection
**The framework:** company-profile JSON in → applicable-framework list out with dependency graph.
**Deterministic logic:**
- Medical device → ISO 13485 + ISO 14971 + (EU MDR 745 if EU market) + (FDA QSR if US market)
- Customer-facing AI → ISO 42001 + EU AI Act (if EU users) + GDPR (if personal data)
- B2B SaaS with enterprise customers → SOC 2 + ISO 27001 (often required for procurement)
- EU customers + personal data → GDPR mandatory
- Highly regulated industry (financial, health) → additional sectoral overlays
**Run** `framework_selector.py` to apply the decision rules.
### 2. Cross-Framework Control Mapping
**The framework:** for each selected framework, parse its control library; compute overlap with other selected frameworks.
**Per merged-control output:**
- Mapping confidence (HIGH / MEDIUM / LOW)
- Evidence-reuse opportunity (single artefact satisfies N controls)
- Per-framework citation
- Implementation guidance reusable across frameworks
**Densest known overlap:** ISO 27001 Annex A ↔ SOC 2 Trust Services Criteria — historically ~75% control coverage shared. Adding ISO 42001 brings AI-specific controls; adding GDPR brings privacy-specific.
**Run** `cross_framework_mapper.py` with framework control libraries.
### 3. Audit Simulation
**The framework:** generate a realistic mock internal audit per ISO 19011 + IIA IPPF standards.
**Per audit output:**
- 8–15 finding scenarios per ISO 19011 typical depth
- `ra-qm-team/skills/fda-consultant-specialist/` — FDA QSR deep-dive
- `ra-qm-team/skills/mdr-745-specialist/` — EU MDR 745 deep-dive
- `ra-qm-team/skills/risk-management-specialist/` — ISO 14971 deep-dive
- `c-level-advisor/chief-ai-officer-advisor/` — Executive AI risk decisions (build-vs-buy, model selection)
- `c-level-advisor/skills/general-counsel-advisor/` — Legal review for novel cases
## References
- [compliance_os_pattern.md](references/compliance_os_pattern.md) — The meta-framework architecture (configure → map → simulate → consolidate → review); when to use vs not
- [cross_framework_overlap.md](references/cross_framework_overlap.md) — The 9-framework × control-family overlap table with mapping confidence (Phase 3 expands to 12 frameworks via `cross_framework_mapper.py`)
- [audit_simulation_methodology.md](references/audit_simulation_methodology.md) — ISO 19011 + IIA IPPF + AICPA AT-C audit-simulation principles + severity distribution heuristics
- [evidence_artifact_reuse_index.md](references/evidence_artifact_reuse_index.md) — Empirically-derived reuse-leverage ranking across all 12 frameworks (Phase 3)
## Phase 3 Asset: Mock Audit Scenario Library
`assets/mock_audit_library.json` — 205 pre-built finding scenarios spanning 12 frameworks + 26 themes + 4 severity levels (34 critical, 88 major, 54 minor, 29 observation). Each scenario tags applicable frameworks; cross-reference `scripts/cross_framework_mapper.py` merged-controls catalogue to resolve framework-specific control IDs. Use as input to enrich `audit_simulator.py` mock audits, as a training resource for new internal auditors, or as the seed for finding-pattern detection across multi-framework programmes.