菜单
Generate editable draw.io diagrams (.drawio, .drawio.svg, .drawio.png) from text, images, Excel, or Markdown. Use for architecture diagrams, flowcharts, sequence diagrams, swimlanes, and Azure/AWS cloud diagrams.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/clcc2019/dsflow --skill drawio-diagram-forge命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Calculate incident impact, detection and recovery durations, classify incidents as L0-L3 from service criticality and impact inputs, compute weighted SLA impact and derived availability, and generate post-incident Markdown reports. Use for SLA calculations, incident severity assessment, outage-duration review, availability summaries, postmortems, incident reports, and remediation tracking.
云原生 SRE 值班助理和巡检编排技能。用于基础设施早检、Kubernetes 集群健康检查、Ceph 存储巡检、计算集群巡检、网关故障初筛、异常证据汇总和值班日报生成。触发场景：用户要求早检、巡检、检查集群是否正常、检查 Ceph、检查计算集群、排查网关错误或生成基础设施健康报告。
Create, review, tune, and validate production-grade Prometheus alerting rules and Kubernetes PrometheusRule resources. Use when writing or repairing alert rule YAML, designing PromQL alert expressions, recommending defensible thresholds and for durations, building SLO/error-budget burn-rate alerts, reducing alert noise, standardizing severity/labels/annotations, adding promtool tests, or reviewing an existing Prometheus rule catalog. 用户要求创建、评审或优化 Prometheus 告警规则、PromQL、告警阈值、告警降噪时使用。
基于 SOC 职业分类
正在显示 SKILL.md
| name | drawio-diagram-forge |
| description | Generate editable draw.io diagrams (.drawio, .drawio.svg, .drawio.png) from text, images, Excel, or Markdown. Use for architecture diagrams, flowcharts, sequence diagrams, swimlanes, and Azure/AWS cloud diagrams. |
Generate editable draw.io diagrams as XML/mxGraphModel. Prefer .drawio for stability; use .drawio.svg for embedding in Markdown or web pages.
scripts/validate_drawio.py when available.outputs/.For complex diagrams, use the orchestrated flow: input analysis, manifest/review, XML generation, validation, and targeted repair.
*.drawio: native draw.io, recommended.*.drawio.svg: SVG with draw.io metadata, useful for Markdown/Web.*.drawio.png: PNG with draw.io metadata.90-100: deliver.85-89: deliver and note minor issues.70-84: repair and retry.50-69: simplify.30-49: deliver partial result.0-29: ask for clarification.Iteration limits: manifest revisions 2, XML/SVG revisions 2, total revisions 4, total timeout 45 minutes.
Detect provider from input terms:
Azure, Microsoft Cloud, App Service, Azure AD, VNET, AKS, Key Vault.AWS, Amazon, EC2, Lambda, S3, RDS, VPC, EKS, DynamoDB.GCP, Google Cloud, Cloud Run, BigQuery, GKE, Cloud Functions.Alibaba Cloud, 阿里云, ECS, OSS, MaxCompute.IBM Cloud, IBM Watson, IBM OpenShift.Cisco, Meraki, ACI, Nexus, ISE.Provider style formats:
image=img/lib/azure2/{category}/{Icon}.svgshape=mxgraph.aws4.resourceIcon;resIcon=mxgraph.aws4.{icon}shape=mxgraph.gcp2.{icon}shape=mxgraph.alibabacloud.{icon}image=img/lib/ibm/{category}/{icon}.svgshape=mxgraph.cisco19.{icon}For unknown services, use a generic labeled shape.
Azure requirement: do not use shape=mxgraph.azure.*; use image=img/lib/azure2/.../*.svg so VS Code and draw.io render correctly.
To view cloud icons in draw.io, enable Azure/AWS shapes via + More Shapes.
mxCell id="0" root and mxCell id="1" default parent.mxCell per node and one edge mxCell per relationship.2 + nodes + edges.Load only as needed:
references/mxcell-structure.md: mxCell XML structure.references/cloud-icons.md: Azure/AWS icon paths and examples.references/style-guide.md: node colors and edge styles.scripts/validate_drawio.py: mxCell validation.