Enterprise Agent Ops

SkillMonitoring & ops

Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Enterprise Agent Ops skill

What this skill tells your AI

The instructions your AI receives, as published by mturac/everything-openai-codex in skills/enterprise-agent-ops/SKILL.md and read by ahel’s review.

Use this skill for cloud-hosted or continuously running agent systems that need operational controls beyond single CLI sessions.

Operational Domains

  1. runtime lifecycle (start, pause, stop, restart)
  2. observability (logs, metrics, traces)
  3. safety controls (scopes, permissions, kill switches)
  4. change management (rollout, rollback, audit)

Baseline Controls

  • immutable deployment artifacts
  • least-privilege credentials
  • environment-level secret injection
  • hard timeout and retry budgets
  • audit log for high-risk actions

Metrics to Track

  • success rate
  • mean retries per task
  • time to recovery
  • cost per successful task
  • failure class distribution

Incident Pattern

When failure spikes:

  1. freeze new rollout
  2. capture representative traces
  3. isolate failing route
  4. patch with smallest safe change
  5. run regression + security checks
  6. resume gradually

Deployment Integrations

This skill pairs with:

  • PM2 workflows
  • systemd services
  • container orchestrators
  • CI/CD gates

Signals

GitHub stars
90
Forks
2
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
enterprise-agent-ops-mturac
Source
github.com/mturac/everything-openai-codex