github-actions
创建或维护 Rust 项目的 GitHub Actions CI、app/Tauri/Docker tag release workflow，并把 Docker 部署文件叠加到已有 server/client 项目。用于 `.github/workflows/*.yml`、release assets、Dockerfile、compose 和复制脚本。
Works with
--- name: github-actions description: 创建或维护 Rust 项目的 GitHub Actions CI、app/Tauri/Docker tag release workflow，并把 Docker 部署文件叠加到已有 server/client 项目。用于 `.github/workflows/*.yml`、release assets、Dockerfile、compose 和复制脚本。 license: MIT --- # GitHub Actions 优先使用 `scripts/copy_assets.py` 复制最接近的 asset。asset 是执行规则来源；除非用户明确要求，不要从头重写 workflow。 - 说明文字使用中文；GitHub Actions 字段、命令、文件名和固定关键词保持原文。 - Docker assets 是已有项目的部署叠加层，不创建 Rust、Tauri 或 frontend 应用源码。 - 复制前验证目标项目和全部冲突；验证失败时不写入任何文件。 - 默认不覆盖已有文件；只有用户明确要求时使用 `--force`。 ## 复制命令 在目标项目根目录外或任意目录执行： ```bash python3 <skill-path>/scripts/copy_assets.py ci --target <project-root> python3 <skill-path>/scripts/copy_assets.py app --target <project-root> --app-bin <binary-name> python3 <skill-path>/scripts/copy_assets.py tauri --target <project-root> python3 <skill-path>/scripts/copy_assets.py docker --target <project-root> --server-bin <binary-name> [--with-client] ``` 前置条件： - `ci`、`app`：目标根目录存在 `Cargo.toml`。 - `tauri`：存在 `package.json`、`bun.lock` 和 `src-tauri/Cargo.toml`。 - `docker`：存在 `server/Cargo.toml`；使用 `--with-client` 时还要存在 `client/package.json` 和 `client/bun.lock`。 复制完成后，按目标项目实际命令审查 workflow 并运行 `actionlint`。Action 使用完整 commit SHA 固定版本，并在同行注释对应 release tag。
More Deployment & CI/CD skills
azure-enterprise-infra-planner
microsoft/azure-skills
Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.
azure-kubernetes-app-deploy
microsoft/azure-skills
Use when deploying an existing web application or API to an already-running Azure Kubernetes Service cluster. Detects the framework, generates a Dockerfile and Kubernetes manifests, validates against AKS Deployment Safeguards, and deploys with verification. WHEN: deploy app to AKS, deploy to existing AKS cluster, containerize app for Kubernetes, generate K8s manifests for Azure, set up CI/CD for AKS, my AKS deployment is failing safeguard checks, I have a Django/Express/Spring Boot app to run on AKS. DO NOT USE FOR: creating or provisioning an AKS cluster (use azure-kubernetes), assessing migration to AKS Automatic (use azure-kubernetes-automatic-readiness), or deploying to non-AKS targets like Web Apps, Container Apps, or Functions.
finetuning
microsoft/azure-skills
Fine-tune models on Microsoft Foundry using SFT (supervised), DPO (preference), or RFT (reinforcement with graders). Covers dataset preparation, training job submission, deployment, and evaluation. USE FOR: fine-tune, SFT, DPO, RFT, training data, grader, distillation, fine-tuned model, training job, large file upload, calibrate grader, deploy fine-tuned model, evaluate fine-tuned model. DO NOT USE FOR: general model deployment without fine-tuning (use deploy-model), agent creation (use agents), prompt optimization without training (use prompt-optimizer).
