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Best practices for writing reliable Pulumi programs. Covers Output handling, resource dependencies, component structure, secrets management, safe refactoring with aliases, and deployment workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Guide for authoring Pulumi ComponentResource classes. Use when creating reusable infrastructure components, designing component interfaces, setting up multi-language support, or distributing component packages.

日本語の概要は準備中です。原文の説明を表示しています。

Convert an AWS CDK application to Pulumi. This skill MUST be loaded whenever a user requests migration or conversion of a CDK application to Pulumi.

日本語の概要は準備中です。原文の説明を表示しています。

Defines service level objectives, creates error budget policies, designs incident response procedures, develops capacity models, and produces monitoring configurations and automation scripts for production systems. Use when defining SLIs/SLOs, managing error budgets, building reliable systems at scale, incident management, chaos engineering, toil reduction, or capacity planning.

日本語の概要は準備中です。原文の説明を表示しています。

Convert or migrate Azure ARM (Azure Resource Manager) templates, Bicep templates, or code to Pulumi, including importing existing Azure resources. This skill MUST be loaded whenever a user requests migration, conversion, or import of ARM templates, Bicep templates, ARM code, Bicep code, or Azure resources to Pulumi.

日本語の概要は準備中です。原文の説明を表示しています。

Use when deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.

日本語の概要は準備中です。原文の説明を表示しています。

Creates Dockerfiles, configures CI/CD pipelines, writes Kubernetes manifests, and generates Terraform/Pulumi infrastructure templates. Handles deployment automation, GitOps configuration, incident response runbooks, and internal developer platform tooling. Use when setting up CI/CD pipelines, containerizing applications, managing infrastructure as code, deploying to Kubernetes clusters, configuring cloud platforms, automating releases, or responding to production incidents. Invoke for pipelines, Docker, Kubernetes, GitOps, Terraform, GitHub Actions, on-call, or platform engineering.

日本語の概要は準備中です。原文の説明を表示しています。

Manages cloud infrastructure through natural language conversations with Pulumi Neo, an AI agent for platform engineers. Enables infrastructure analysis, resource provisioning, stack deployment, and configuration management via conversational AI. Use when creating Neo tasks, requesting infrastructure analysis, automating cloud deployments, managing infrastructure as code (IaC), provisioning AWS/Azure/GCP resources, managing infrastructure through natural language prompts, reviewing PRs with Neo, handling Neo approval workflows, or checking Neo task status and events. Also use when the user mentions "Pulumi Neo", "Neo task", "Neo agent", or wants AI-assisted infrastructure management.

日本語の概要は準備中です。原文の説明を表示しています。

Convert an AWS CloudFormation stack or template to Pulumi. This skill MUST be loaded whenever a user requests migration or conversion of CloudFormation to Pulumi.

日本語の概要は準備中です。原文の説明を表示しています。

Creates Pulumi infrastructure-as-code projects in Go, configures OIDC authentication, integrates with Pulumi ESC for centralized secrets and configuration management, and builds multi-language component resources. Use when setting up Pulumi Go projects, writing infrastructure code with Go, configuring OIDC for Pulumi, using Pulumi ESC with Go, automating cloud infrastructure with Golang, creating reusable Pulumi components in Go, or working with pulumi-go-provider. Also use when the user mentions Pulumi with Go/Golang, AWS/Azure/GCP infrastructure in Go, or Go-based ComponentResource patterns.

日本語の概要は準備中です。原文の説明を表示しています。

Opens a pull request, publishing the current branch as a PR. TRIGGER when: the user wants to open a pull request, publish the current branch as a PR, or take the current work through to an open PR. DO NOT TRIGGER when: only committing changes → commit; babysitting CI after the PR is already open → monitoring-pull-requests.

日本語の概要は準備中です。原文の説明を表示しています。

Rebases a feature branch onto its latest base, resolving conflicts while preserving the intent of local changes, optionally force-pushing and watching CI afterward. TRIGGER when: the user wants to rebase a feature branch, update a branch against its base, or replay local work on top of the latest upstream. DO NOT TRIGGER when: merging a release branch into dev → merging-branches; only watching CI on an already-open PR → monitoring-pull-requests.

日本語の概要は準備中です。原文の説明を表示しています。

Watches an open pull request's CI until green and fixes failing checks. TRIGGER when: the user wants to watch a pull request's CI, babysit a PR until it goes green, or fix failing CI checks on an open PR. DO NOT TRIGGER when: opening the PR in the first place → pr; rebasing the branch onto its base → rebase.

日本語の概要は準備中です。原文の説明を表示しています。

Orchestrate AI coding agents (Claude Code, Codex, OpenCode) in isolated sandboxes using the @ai-hero/sandcastle SDK. Use when the user needs to (1) run agents AFK in Docker/Podman containers, (2) build multi-agent pipelines with plan-execute-review patterns, (3) run parallel agents on separate worktrees, (4) create iterative agent loops with maxIterations, (5) extract structured output from agent runs, (6) set up sandcastle in a new or existing project, or (7) write prompt files with template args and shell expressions.

日本語の概要は準備中です。原文の説明を表示しています。

Set up and run local LLMs with Harbor. Use when the user wants to run models locally, install Harbor, start Open WebUI, llama.cpp, Ollama, vLLM, Docker Model Runner, MLX, or oMLX, pull GGUF or HuggingFace models, add SearXNG web search, Speaches TTS/STT, or Open Terminal code execution, launch Codex/Claude/Grok/OpenCode against a Harbor backend, or troubleshoot GPU, VRAM, and service startup.

日本語の概要は準備中です。原文の説明を表示しています。

Generates production-ready Terraform files for AWS infrastructure. Writes complete .tf files for any cloud architecture — no deployment, just file generation.

日本語の概要は準備中です。原文の説明を表示しています。

Set up mobile CI/CD pipelines for Flutter, React Native, or native iOS/Android — GitHub Actions workflows for testing, code signing, TestFlight/Play Store distribution, build number management, Fastlane integration, and artifact retention

日本語の概要は準備中です。原文の説明を表示しています。

Set up a complete mobile publishing pipeline — chains CI/CD workflow generation, iOS App Store publishing via Fastlane, Google Play Store publishing, and analytics verification into an end-to-end release automation. Use for Flutter, React Native, or native iOS/Android apps ready for store submission.

日本語の概要は準備中です。原文の説明を表示しています。

Audit codebases for leaked secrets and hardcoded credentials, generate .env templates, configure secrets management with AWS Secrets Manager, Vault, Doppler, or GCP Secret Manager, set up credential rotation, and integrate secrets into CI/CD pipelines via OIDC federation

日本語の概要は準備中です。原文の説明を表示しています。

Configure a CDN with optimized caching, SSL/TLS, security headers, and cache invalidation — auto-detects hosting provider and app type, generates CloudFront, Cloudflare, or Vercel config with per-content-type cache rules, edge functions, and compression. Use when deploying a static site, SPA, SSR app, or adding a CDN layer to an existing API.

日本語の概要は準備中です。原文の説明を表示しています。

Provision free LLM API keys from 20+ providers. Health-checks existing keys, opens signup pages, validates new keys, and saves them to your project.

日本語の概要は準備中です。原文の説明を表示しています。

Detect project stack and generate GitHub Actions CI/CD workflows — PR checks with lint/test/build/security, deploy pipelines for Vercel/AWS/GCP/Fly/Docker, dependency caching, matrix testing, preview deploys, and Dependabot config

日本語の概要は準備中です。原文の説明を表示しています。

Emergency bug fix pipeline — diagnose, fix, test, commit, push, and PR in 2 iterations max. Speed over perfection.

日本語の概要は準備中です。原文の説明を表示しています。

Set up application observability with Prometheus, Grafana, Datadog, or CloudWatch — instrument metrics endpoints, configure Golden Signal dashboards, define alert rules with burn-rate SLOs, and add structured logging

日本語の概要は準備中です。原文の説明を表示しています。