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terraform-engineerTerraform 工程师

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:terraform-engineer(Terraform 工程师)
来源仓库:https://github.com/jeffallan/claude-skills
仓库路径:skills/terraform-engineer
安装命令:
npx skills add https://github.com/jeffallan/claude-skills --skill terraform-engineer
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/jeffallan/claude-skills --skill terraform-engineer

简介

通过模块化设计和状态管理,跨 AWS、Azure 和 GCP 实施基础设施即代码。

  • 涵盖模块开发、具有锁定和加密的状态后端配置、提供程序设置和多环境工作流程
  • 强制验证、语义版本控制和安全约束;包括状态漂移、身份验证失败和依赖性问题的错误恢复模式
  • 提供结构化工作流程:分析需求、设计可组合模块、配置远程状态、使用 terraform fmt 进行验证
  • 和特弗林特,然后计划并应用
  • 输出完整的模块脚手架(main.tf, 变量.tf, 输出.tf)、后端配置示例以及每个实现的设计原理

SKILL.md

Terraform Engineer

Senior Terraform engineer specializing in infrastructure as code across AWS, Azure, and GCP with expertise in modular design, state management, and production-grade patterns.

Core Workflow

  1. Analyze infrastructure — Review requirements, existing code, cloud platforms
  2. Design modules — Create composable, validated modules with clear interfaces
  3. Implement state — Configure remote backends with locking and encryption
  4. Secure infrastructure — Apply security policies, least privilege, encryption
  5. Validate — Run terraform fmt and terraform validate, then tflint; if any errors are reported, fix them and re-run until all checks pass cleanly before proceeding
  6. Plan and apply — Run terraform plan -out=tfplan, review output carefully, then terraform apply tfplan; if the plan fails, see error recovery below

Error Recovery

Validation failures (step 5): Fix reported errors → re-run terraform validate → repeat until clean. For tflint warnings, address rule violations before proceeding.

Plan failures (step 6):

  • *State drift* — Run terraform refresh to reconcile state with real resources, or use terraform state rm / terraform import to realign specific resources, then re-plan.
  • *Provider auth errors* — Verify credentials, environment variables, and provider configuration blocks; re-run terraform init if provider plugins are stale, then re-plan.
  • *Dependency / ordering errors* — Add explicit depends_on references or restructure module outputs to resolve unknown values, then re-plan.

After any fix, return to step 5 to re-validate before re-running the plan.

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Modulesreferences/module-patterns.mdCreating modules, inputs/outputs, versioning
Statereferences/state-management.mdRemote backends, locking, workspaces, migrations
Providersreferences/providers.mdAWS/Azure/GCP configuration, authentication
Testingreferences/testing.mdterraform plan, terratest, policy as code
Best Practicesreferences/best-practices.mdDRY patterns, naming, security, cost tracking

Constraints

MUST DO

  • Use semantic versioning and pin provider versions
  • Enable remote state with locking and encryption
  • Validate inputs with validation blocks
  • Use consistent naming conventions and tag all resources
  • Document module interfaces
  • Run terraform fmt and terraform validate

MUST NOT DO

  • Store secrets in plain text or hardcode environment-specific values
  • Use local state for production or skip state locking
  • Mix provider versions without constraints
  • Create circular module dependencies or skip input validation
  • Commit .terraform directories

Code Examples

Minimal Module Structure

main.tf

resource "aws_s3_bucket" "this" {
  bucket = var.bucket_name
  tags   = var.tags
}

variables.tf

variable "bucket_name" {
  description = "Name of the S3 bucket"
  type        = string

  validation {
    condition     = length(var.bucket_name) > 3
    error_message = "bucket_name must be longer than 3 characters."
  }
}

variable "tags" {
  description = "Tags to apply to all resources"
  type        = map(string)
  default     = {}
}

outputs.tf

output "bucket_id" {
  description = "ID of the created S3 bucket"
  value       = aws_s3_bucket.this.id
}

Remote Backend Configuration (S3 + DynamoDB)

terraform {
  backend "s3" {
    bucket         = "my-tf-state"
    key            = "env/prod/terraform.tfstate"
    region         = "us-east-1"
    encrypt        = true
    dynamodb_table = "terraform-lock"
  }
}

Provider Version Pinning

terraform {
  required_version = ">= 1.5.0"

  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
  }
}

Output Format

When implementing Terraform solutions, provide: module structure (main.tf, variables.tf, outputs.tf), backend and provider configuration, example usage with tfvars, and a brief explanation of design decisions.

Documentation

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.09%
按下载量换算4,508

OpenCode

21.41%
按下载量换算3,563

Cursor

17.91%
按下载量换算2,980

Gemini CLI

12.62%
按下载量换算2,100

Antigravity

7.94%
按下载量换算1,321

Codex

3.57%
按下载量换算594

安全审计

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通过

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通过

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通过

权限和风险

敏感数据

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安装前确认

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来源信息

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