mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-17 23:09:35 +00:00
Governance layer (14 docs): - MASTER_OPERATING_PROMPT.md — operating constitution (five planes, six tracks, policy classes) - docs/ai-operating-model.md — five-plane architecture (Decision/Execution/Trust/Data/Operating) - docs/dealix-six-tracks.md — six strategic tracks (Revenue/Intelligence/Compliance/Expansion/Operations/Trust) - docs/governance/execution-fabric.md — OpenClaw execution plane deep dive - docs/governance/trust-fabric.md — trust plane with contradiction engine + evidence packs - docs/governance/saudi-compliance-and-ai-governance.md — PDPL/ZATCA/SDAIA/NCA live controls - docs/governance/technology-radar-tier1.md — Core/Strong/Pilot/Watch/Hold classification - docs/governance/partnership-os.md — alliance lifecycle management - docs/governance/ma-os.md — M&A corporate development lifecycle - docs/governance/expansion-os.md — geographic and vertical growth - docs/governance/pmi-os.md — post-merger integration framework - docs/governance/executive-board-os.md — executive decision surfaces - docs/execution-matrix-90d-tier1.md — 90-day sprint execution plan - docs/adr/0001-tier1-execution-policy-spikes.md — 8 architectural decisions Backend (3 models, 6 services, 8 API routes): - Contradiction Engine — detect/track system conflicts - Evidence Pack System — tamper-evident audit proof with SHA256 - Saudi Compliance Matrix — live PDPL/ZATCA/SDAIA/NCA controls - Executive Room — unified executive decision surface - Connector Governance — integration health monitoring - Model Routing Dashboard — LLM provider metrics - Forecast Control Center — actual vs forecast across tracks - Approval Center — enhanced approval queue with SLA Frontend (9 components): - Executive Room, Evidence Pack Viewer, Approval Center - Connector Governance Board, Saudi Compliance Dashboard - Actual vs Forecast Dashboard, Risk Heatmap - Policy Violations Board, Partner Pipeline Board Tooling: - scripts/architecture_brief.py — preflight validation (40/40 checks pass) - Updated CLAUDE.md and AGENTS.md with governance references https://claude.ai/code/session_01W1rJthWDkasijTdXCfxVHs
49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
"""Compliance Control — live Saudi/GCC regulatory controls for compliance matrix."""
|
|
|
|
from __future__ import annotations
|
|
|
|
import enum
|
|
|
|
from sqlalchemy import Column, DateTime, Enum, String, Text
|
|
from sqlalchemy.dialects.postgresql import JSONB
|
|
|
|
from app.models.base import TenantModel
|
|
|
|
|
|
class ComplianceCategory(str, enum.Enum):
|
|
PDPL = "pdpl"
|
|
ZATCA = "zatca"
|
|
SDAIA = "sdaia"
|
|
NCA = "nca"
|
|
SECTOR_SPECIFIC = "sector_specific"
|
|
|
|
|
|
class ComplianceStatus(str, enum.Enum):
|
|
COMPLIANT = "compliant"
|
|
NON_COMPLIANT = "non_compliant"
|
|
PARTIAL = "partial"
|
|
NOT_APPLICABLE = "not_applicable"
|
|
|
|
|
|
class RiskLevel(str, enum.Enum):
|
|
CRITICAL = "critical"
|
|
HIGH = "high"
|
|
MEDIUM = "medium"
|
|
LOW = "low"
|
|
|
|
|
|
class ComplianceControl(TenantModel):
|
|
__tablename__ = "compliance_controls"
|
|
|
|
control_id = Column(String(20), nullable=False, index=True) # e.g. PDPL-C01
|
|
control_name = Column(String(255), nullable=False)
|
|
control_name_ar = Column(String(255), nullable=True)
|
|
category = Column(Enum(ComplianceCategory), nullable=False)
|
|
status = Column(Enum(ComplianceStatus), nullable=False, default=ComplianceStatus.PARTIAL)
|
|
evidence_source = Column(String(255), nullable=True) # which service provides the live check
|
|
last_checked_at = Column(DateTime(timezone=True), nullable=True)
|
|
last_result = Column(JSONB, default=dict)
|
|
remediation_plan = Column(Text, nullable=True)
|
|
owner = Column(String(100), nullable=True)
|
|
risk_level = Column(Enum(RiskLevel), nullable=False, default=RiskLevel.MEDIUM)
|