AI Ops Audit Toolkit

ready

For: Engineering teams running AI agents in production — platform teams, MLOps orgs, and any shop where autonomous agents touch repos, databases, or infrastructure.

Your AI agents push code, run jobs, and touch production — but you have no audit trail, no policy enforcement, no health checks, and no way to prove compliance. One rogue agent action and you're debugging blind.

What you get

A battle-tested governance framework for AI agent operations: policy engine with 25+ pre-built laws, command risk classifier, secret detector, path guard, repo health analyzer, action receipt audit trail, job queue, worker loop, CLI tool, PostgreSQL schema (14 tables), 159 passing tests, and a full compliance checklist. Drop-in Python codebase — adapt to your agent stack in hours.

Preview

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What you get

📝 Worksheets & sample data

• assets/config-template.yaml

🧰 Scripts & samples

• src/register_hx370.py
• src/node_registry.py
• src/actions/memory.py
• src/actions/quick_actions.py
• src/actions/__init__.py
• src/actions/action_receipt.py
• src/actions/locking.py
• src/actions/autofix.py
• src/actions/action_pack.py
• src/actions/autonomy.py
• src/intelligence/query.py
• src/intelligence/cross_repo.py

Support and assurance

The product page and buyer documents define the delivered materials, setup expectations, and support path. Contact us with the product name and the step that failed; never send credentials or private customer data.