xint
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
Agent Ops Runbook
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
SkillHub CLI
skillhub install 1kalin/afrexai-agent-runbook打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。
将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。
Generate a production-ready operations runbook for deploying AI agents. Covers pre-deployment checklists, shadow mode → supervised → autonomous rollout stages, monitoring dashboards, rollback procedures, cost management, and incident response templates.
When the user asks for an agent ops runbook or deployment plan:
Ask which agent function they're deploying (support, sales, document processing, etc.)
Ask about their risk tolerance (conservative, moderate, aggressive rollout)
Generate a complete runbook with:
Include specific metric targets:
Flag risks specific to their industry (compliance, PII, financial accuracy)
Output format: Markdown document ready to share with engineering and ops teams.
这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。
Production deployment runbooks for AI agent systems. Not theory — actual procedures your ops team can use.
Generates complete runbooks covering:
# Agent Ops Runbook Generate a production-ready operations runbook for deploying AI agents. Covers pre-deployment checklists, shadow mode → supervised → autonomous rollout stages, monitoring dashboards, rollback procedures, cost management, and incident response templates. ## When to Use - Deploying an AI agent to production - Building monitoring and alerting for agent systems - Creating rollback procedures for autonomous workflows - Estimating and controlling agent operational costs ## Instructions When the user asks for an agent ops runbook or deployment plan: 1. Ask which agent function they're deploying (support, sales, document processing, etc.) 2. Ask about their risk tolerance (conservative, moderate, aggressive rollout) 3. Generate a complete runbook with: - Pre-deployment checklist specific to their function - 3-stage rollout plan with metrics and gates - Monitoring alerts (critical + warning thresholds) - Rollback procedures (3 levels: prompt, feature, full) - Cost estimates based on their expected volume - 90-day implementation timeline - Incident response template 4. Include specific metric targets: - Accuracy vs human baseline: >90% - Error rate: <2% - Cost per task benchmarks by function - Human escalation rate: 5-15% 5. Flag risks specific to their industry (compliance, PII, financial accuracy) Output format: Markdown document ready to share with engineering and ops teams.
# Agent Ops Runbook Generator Production deployment runbooks for AI agent systems. Not theory — actual procedures your ops team can use. Generates complete runbooks covering: - Pre-deployment checklists - Shadow → Supervised → Autonomous rollout stages - Real-time monitoring and alerting configs - 3-level rollback procedures - Cost management and optimization - Incident response templates - 90-day implementation timelines ## Get More - [AI Revenue Calculator](https://afrexai-cto.github.io/ai-revenue-calculator/) — free ROI analysis - [Agent Setup Wizard](https://afrexai-cto.github.io/agent-setup/) — working configs in 5 minutes - [Industry Context Packs](https://afrexai-cto.github.io/context-packs/) — pre-built agent configs for 10 industries ($47 each)
X Intelligence CLI — search, monitor, analyze, and engage on X/Twitter. TypeScript + Bun. AI agent skill.
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