Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.
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sayasaya8039/ZWG_Terminal22026年6月8日 更新
免费在 GitHub 公开
enterprise-agent-ops
Operate long-lived agent workloads with observability, security boundaries, and lifecycle management.
中文简介正在准备中。当前显示原文说明。
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SKILL.md（原文）
安装前可以查看交给 AI 代理的指令内容。
Enterprise Agent Ops
Use this skill for cloud-hosted or continuously running agent systems that need operational controls beyond single CLI sessions.
Operational Domains
- runtime lifecycle (start, pause, stop, restart)
- observability (logs, metrics, traces)
- safety controls (scopes, permissions, kill switches)
- 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:
- freeze new rollout
- capture representative traces
- isolate failing route
- patch with smallest safe change
- run regression + security checks
- resume gradually
Deployment Integrations
This skill pairs with:
- PM2 workflows
- systemd services
- container orchestrators
- CI/CD gates
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