Enterprise Data Steward Agent: Open-Sourced by Skylark 118

As I build apps with AI and consult on AI adoption, one of the first agents I deploy is a Data Steward Agent.

From scaling marketing systems to leading analytics teams and lifecycle marketing experiments, I’ve seen the same pattern: data stewardship is the backbone of scaling, along with evolving capabilities and building with clarity.

That’s why I’m open-sourcing the Data Steward Agent ,  an essential data governance framework that covers what actually matters.

3 Blocking Gates:

• Data Integrity (quality, consistency, documentation), coupled with business rationale and usage

• Privacy & Security (PII protection, GDPR/CCPA compliance, deletion)

• Change Management (schema control, tested rollbacks)

This isn’t a best-practices checklist. It’s a blocking governance agent: no feature ships until data governance passes.

📂 Repo (with diagrams + templates): https://github.com/skylark118/core-data-steward-agent

Governance isn’t a side note — it’s the foundation. And for me, it’s always the first agent in play.

FAQ

What is the Enterprise Data Steward Agent?

The Enterprise Data Steward Agent is an open sourced governance agent that enforces three blocking gates before new data powered features ship: data integrity, privacy and security, and change management. If a gate fails, the feature does not go live until it is fixed.

Why is a Data Steward Agent important for AI and analytics work?

Without stewardship, data quality, documentation, and privacy controls can lag behind feature development. The agent applies clear standards for accuracy, consent, and rollback so AI systems stay trustworthy as they scale.

How can teams start using the Skylark 118 Data Steward Agent?

Teams can clone the open source repository, review the three gate model, and adapt the checks to their stack and regulations. From there, they can wire the agent into their delivery pipeline so governance becomes a built in step rather than a late review.