A comprehensive assessment and remediation tool designed to score organizational data maturity across six mission-critical domains.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install afrexai-data-governance
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install afrexai-data-governance using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Data Governance Framework?
The Data Governance Framework is a technical evaluation system designed to help organizations systematically identify and fix gaps in their data strategy. By leveraging Openclaw Skills, teams can perform deep-dive audits into data quality, cataloging, access controls, and compliance mapping. The framework is particularly uniquely positioned to address modern challenges, including training data provenance and PII handling within agentic workflows.
This skill serves as a bridge between raw data operations and executive-level risk management. It provides a standardized scoring mechanism that translates complex technical controls into actionable business intelligence, allowing stakeholders to prioritize remediation efforts based on actual financial and regulatory risks. Integrating this into your Openclaw Skills library ensures that your data infrastructure remains robust, compliant, and ready for AI scaling.
Data Governance Framework Use Cases
- Conducting comprehensive internal audits to prepare for GDPR, HIPAA, or CCPA certifications.
- Evaluating the security posture of role-based access controls and least-privilege enforcement.
- Monitoring AI agent workflows for PII detection, hallucination, and model input/output logging.
- Benchmarking organizational data maturity against industry-specific standards in Finance, Healthcare, and SaaS.
- Generating automated remediation roadmaps to address critical compliance gaps and data quality failures.
How Data Governance Framework Works
- Define the scope of the assessment by selecting priority domains or choosing a full six-domain audit.
- Evaluate 8 specific technical and administrative controls for each domain using a standardized 0-3 maturity scale.
- Aggregate the scores to calculate a domain-specific percentage and an overall governance maturity score.
- Map the results against the scoring interpretation matrix to identify critical, developing, or managed areas.
- Generate a prioritized remediation roadmap that addresses compliance and security risks first, followed by operational optimizations.
Data Governance Framework Setup
To begin using this framework within your environment, follow these initialization steps:
# Install the governance module via the CLI
openclaw install data-governance-framework
# Initiate a new assessment for your organization
openclaw run assessment --init --all-domains
# View the current scoring matrix and baseline
openclaw report view governance-summary
Data Governance Framework Data Schema & Taxonomy
The framework organizes its findings into a structured metadata taxonomy to ensure clear reporting and tracking. Data is categorized as follows:
| Data Category | Attributes Tracked | Metadata Sensitivity |
|---|---|---|
| Domain Controls | Implementation status, automation level, SLA thresholds | Internal |
| Compliance Map | Regulation ID, Article mapping, audit trail | Restricted |
| AI Provenance | Training source, consent flags, bias metrics | Confidential |
| Asset Inventory | System ID, lineage path, usage analytics | Internal |
All results are stored in a machine-readable format to allow for integration with BI tools and continuous monitoring dashboards.
Data Governance Framework Advanced Features
- Automated AI Governance: Specialized controls for tracking model input/output logging and agent decision audit trails.
- Financial Risk Modeling: Integrated cost-of-risk tables that calculate potential revenue impact from bad data and regulatory fines.
- Lifecycle Automation: Advanced hooks for hot-to-cold archival pipelines and automated deletion verification.
- Cross-System Reconciliation: Logic for source-to-target matching to ensure data consistency across distributed architectures.
- Industry Benchmarking: Compare your Openclaw Skills assessment results against real-world 2026 industry quartiles.
SKILL.md
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