hashicorp/azure-verified-modules
Azure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.
Azure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.
npx skills add https://github.com/hashicorp/agent-skills/tree/main/skills/azure-verified-modulesAzure Verified Modules (AVM) requirements and best practices for developing certified Azure Terraform modules. Use when creating or reviewing Azure modules that need AVM certification.
This repo contains 15 individual skills — each has its own dedicated page.
Build Amazon Machine Images (AMIs) with Packer using the amazon-ebs builder. Use when creating custom AMIs for EC2 instances.
Build Azure managed images and Azure Compute Gallery images with Packer. Use when creating custom images for Azure VMs.
Use this when scaffolding a new Terraform provider.
Implement Terraform Provider actions using the Plugin Framework. Use when developing imperative operations that execute at lifecycle events (before/after create, update, destroy).
Create, update, and review Terraform provider documentation for Terraform Registry using HashiCorp-recommended patterns, tfplugindocs templates, and schema descriptions. Use when adding or changing provider configuration, resources, data sources, ephemeral resources, list resources, functions, or guides; when validating generated docs; and when troubleshooting missing or incorrect Registry documentation.
Implement Terraform Provider resources and data sources using the Plugin Framework. Use when developing CRUD operations, schema design, state management, and acceptance testing for provider resources.
Terraform provider acceptance test patterns using terraform-plugin-testing with the Plugin Framework. Covers test structure, TestCase/TestStep fields, ConfigStateChecks with custom statecheck.StateCheck implementations, plan checks, CompareValue for cross-step assertions, config helpers, import testing with ImportStateKind, sweepers, and scenario patterns (basic, update, disappears, validation, regression), and ephemeral resource testing with the echoprovider package. Use when writing, reviewing, or debugging provider acceptance tests, including questions about statecheck, plancheck, TestCheckFunc, CheckDestroy, ExpectError, import state verification, ephemeral resources, or how to structure test files.
Push Packer build metadata to HCP Packer registry for tracking and managing image lifecycle. Use when integrating Packer builds with HCP Packer for version control and governance.
Transform monolithic Terraform configurations into reusable, maintainable modules following HashiCorp's module design principles and community best practices.
Guide for running acceptance tests for a Terraform provider. Use this when asked to run an acceptance test or to run a test with the prefix `TestAcc`.
Discover existing cloud resources using Terraform Search queries and bulk import them into Terraform management. Use when bringing unmanaged infrastructure under Terraform control, auditing cloud resources, or migrating to IaC.
Comprehensive guide for working with HashiCorp Terraform Stacks. Use when creating, modifying, or validating Terraform Stack configurations (.tfcomponent.hcl, .tfdeploy.hcl files), working with stack components and deployments from local modules, public registry, or private registry sources, managing multi-region or multi-environment infrastructure, or troubleshooting Terraform Stacks syntax and structure.
Generate Terraform HCL code following HashiCorp's official style conventions and best practices. Use when writing, reviewing, or generating Terraform configurations.
Comprehensive guide for writing and running Terraform tests. Use when creating test files (.tftest.hcl), writing test scenarios with run blocks, validating infrastructure behavior with assertions, mocking providers and data sources, testing module outputs and resource configurations, or troubleshooting Terraform test syntax and execution.
Build Windows images with Packer using WinRM communicator and PowerShell provisioners. Use when creating Windows AMIs, Azure images, or VMware templates.
Production-grade platform for building agentic IM bots - 生产级多平台智能机器人开发平台. 提供 Agent、知识库编排、插件系统 / Bots for Discord / Slack / LINE / Telegram / WeChat(企业微信, 企微智能机器人, 公众号) / 飞书 / 钉钉 / QQ / Satori e.g. Integrated with ChatGPT(GPT), DeepSeek, Dify, n8n, Langflow, Coze, Claude, Gemini, MiniMax, Ollama, SiliconFlow, Moonshot, GLM, openclaw / hermes agent
📄 Convert 29+ file formats to clean Markdown using the Model Context Protocol for seamless integration with AI workflows.
Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations, help choosing the latest model for a use case, or model upgrade and prompt-upgrade guidance; prioritize OpenAI docs MCP tools, use bundled references only as helper context, and restrict any fallback browsing to official OpenAI domains.
Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.
A minimal file-based protocol to coordinate multiple Claude Code instances across separate sessions
When agent sessions generate millions of tokens of conversation history, compression becomes mandatory. The naive approach is aggressive compression to minimize tokens per request.