Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Other
Data Governance Framework
Evaluate and improve your organization's data governance across six domains by scoring controls, identifying risks, and prioritizing remediation actions.
skill openclawclawhub Free
Evaluate and improve your organization's data governance across six domains by scoring controls, identifying risks, and prioritizing remediation actions.
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- 1kalin
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Data Governance Framework
Assess, score, and remediate your organization's data governance posture across 6 domains.
What This Covers
Data Quality โ Completeness, accuracy, consistency, timeliness scoring Data Cataloging โ Asset inventory, lineage tracking, metadata management Access Control โ Role-based permissions, least privilege, data classification (public/internal/confidential/restricted) Compliance Mapping โ GDPR, CCPA, SOX, HIPAA, PCI-DSS, industry-specific regulations Retention & Lifecycle โ Retention policies, archival schedules, deletion procedures, legal hold AI/Agent Data Governance โ Training data provenance, model input/output logging, bias detection, PII handling in agent workflows
How to Use
When asked to assess data governance: Ask which domains are priority (or assess all 6) For each domain, evaluate 8 controls on a 0-3 scale: 0 = Not implemented 1 = Ad hoc / informal 2 = Documented and partially enforced 3 = Automated and continuously monitored Calculate domain score (sum / 24 ร 100) Calculate overall governance score (average of domains) Generate remediation roadmap prioritized by risk
Scoring Interpretation
ScoreRatingAction0-25%CriticalImmediate remediation โ regulatory risk26-50%Developing90-day improvement plan required51-75%ManagedOptimize and automate weak areas76-100%OptimizedMaintain and benchmark against peers
Domain 1: Data Quality Controls
Data profiling automation (duplicate detection, format validation) Quality dashboards with SLA thresholds Root cause analysis for quality failures Stewardship program (assigned data owners per domain) Quality gates in data pipelines (reject bad data at ingestion) Business rule validation (domain-specific logic checks) Cross-system reconciliation (source vs target matching) Quality trend tracking (month-over-month improvement metrics)
Domain 2: Data Cataloging Controls
Automated asset discovery (databases, APIs, files, SaaS) Business glossary with agreed definitions Data lineage tracking (source โ transformation โ consumption) Search and discovery interface for business users Metadata enrichment (tags, classifications, sensitivity labels) Catalog coverage tracking (% of assets documented) Usage analytics (who accesses what, how often) Integration with BI/analytics tools (catalog-aware queries)
Domain 3: Access Control
Role-based access control (RBAC) with regular review Data classification enforcement (labels drive permissions) Least privilege principle (minimal default access) Access request and approval workflows Privileged access management (admin accounts monitored) Access certification (quarterly re-certification of permissions) Anomaly detection (unusual access patterns flagged) De-provisioning automation (access removed on role change/exit)
Domain 4: Compliance Mapping
Regulation inventory (which laws apply, by geography and industry) Control-to-regulation mapping (which controls satisfy which requirements) Data processing records (Article 30 GDPR / equivalent) Consent management (capture, storage, withdrawal tracking) Data subject rights automation (access, deletion, portability) Cross-border transfer compliance (SCCs, adequacy decisions) Breach notification procedures (72-hour GDPR, state-specific) Regular compliance audits (internal + third-party)
Domain 5: Retention & Lifecycle
Retention schedule by data type (contractual, regulatory, operational) Automated archival pipelines (hot โ warm โ cold โ delete) Legal hold management (litigation preservation) Deletion verification (confirmed purge with audit trail) Storage cost optimization (tiered storage aligned to access patterns) Backup and recovery testing (regular restore drills) Data minimization enforcement (collect only what is needed) End-of-life procedures for decommissioned systems
Domain 6: AI/Agent Data Governance
Training data provenance tracking (source, consent, bias review) Model input/output logging (what went in, what came out) PII detection and masking in agent workflows Hallucination monitoring (output accuracy validation) Agent decision audit trail (explainability for automated decisions) Data feedback loops (human review of agent data modifications) Vendor data sharing agreements (what third-party APIs see your data) Synthetic data policies (when and how to use generated data)
Cost of Poor Governance
RiskAverage CostPrevention CostGDPR fine$4.3M (average 2025)$45K-$120K/yearData breach$4.88M (IBM 2025)$60K-$200K/yearFailed audit$150K-$500K remediation$30K-$80K/yearBad data decisions15-25% revenue impact$20K-$60K/yearAI bias incident$2M-$50M (litigation + brand)$25K-$75K/year
Remediation Priority Matrix
Always fix in this order: Compliance gaps โ regulatory fines are existential Access control โ breaches destroy trust overnight AI governance โ fastest-growing risk category Data quality โ garbage in = garbage out at scale Cataloging โ you cannot govern what you cannot find Retention โ storage costs compound, legal risk accumulates
Industry Benchmarks (2026)
IndustryAvg Governance ScoreTop QuartileRegulatory PressureFinancial Services68%85%+Extreme (SOX, PCI, GDPR)Healthcare62%80%+High (HIPAA, FDA, state)SaaS/Tech55%78%+Growing (SOC 2, GDPR, CCPA)Manufacturing45%70%+Moderate (ITAR, ISO)Retail/Ecommerce48%72%+Growing (PCI, CCPA, GDPR)
Next Steps
Need a complete data governance implementation tailored to your industry? Calculate your AI revenue leak Industry context packs โ $47 each Agent setup wizard
Category context
Long-tail utilities that do not fit the current primary taxonomy cleanly.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md