openclaw 网盘下载
OpenClaw

技能详情(站内镜像,无评论)

首页 > 技能库 > Agent Ops Runbook

Generate a detailed operations runbook for deploying AI agents, including rollout stages, monitoring, rollback plans, cost estimates, and incident response t...

开发与 DevOps

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.1.0

统计:⭐ 0 · 383 · 0 current installs · 0 all-time installs

0

安装量(当前) 0

🛡 VirusTotal :良性 · OpenClaw :良性

Package:1kalin/afrexai-agent-runbook

安全扫描(ClawHub)

  • VirusTotal :良性
  • OpenClaw :良性

OpenClaw 评估

This is an instruction-only runbook generator whose requested capabilities, instructions, and metadata are internally consistent and do not ask for extra permissions or install software.

目的

Name and description match the SKILL.md instructions: it exists to generate deployment runbooks and asks only for user inputs to tailor those runbooks. No unrelated binaries, env vars, or credentials are requested.

说明范围

Instructions are narrowly scoped to asking about the agent function and risk tolerance and producing a runbook. They include hardcoded suggested metric targets (e.g., >90% accuracy, <2% error, 5–15% escalation) which may not be appropriate for all domains; users should validate and adjust those thresholds for their context. The instructions do not tell the agent to read local files, transmit data externally, or access other system state.

安装机制

No install spec and no code files — the skill is instruction-only, so nothing will be written to disk or downloaded during install.

证书

The skill requests no environment variables, credentials, or config paths. There is no disproportionate access requested relative to the described functionality.

持久

always is false and the skill is user-invocable; it does not request persistent or elevated platform privileges or modify other skill/system configs.

综合结论

This skill is instruction-only and appears coherent for generating runbooks. Before using it: (1) do not paste production secrets or PII into prompts — the runbook generator will include any data you provide; (2) review and tune the hardcoded metric targets and rollout gates to match your domain and compliance needs (financial, healthcare, etc.); (3) verify any recommended monitoring or automated rollback actions with your ops/security teams b…

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Agent Ops Runbook」。简介:Generate a detailed operations runbook for deploying AI agents, including rollo…。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/1kalin/afrexai-agent-runbook/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

# 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.