技術記事の品質を「伝説の編集者」の視点で厳格にレビューするためのスキル。記事のドラフトが完成した際、既存記事のブラッシュアップ、または「この記事どうかな?」という漠然とした相談に対しても、このスキルを積極的に使用してください。5つの品質の柱(論理性、実用性、読みやすさ、独自性、明確性)に基づいた厳格な採点と、AI臭さを徹底的に排除した「魂の宿る記事」への改善案を提供します。
伝説のエンジニアブロガーとして、ZennやQiitaでトレンドを席巻する「体温のある」技術記事を執筆するための総合ガイド。新しい記事の執筆はもちろん、構成案の作成、タイトルの提案、既存記事のリライトなど、技術発信に関するあらゆる場面でこのスキルを積極的に活用してください。ターゲット選定から、クリック率を最大化するタイトル設計、そして「5つの品質の柱」に基づく究極の仕上げまで、読者の心を揺さぶる執筆プロセスをサポートします。
Expert guide for developing with Floci — the Java/Quarkus-based open-source local AWS emulator. Use this skill whenever someone asks about adding a new AWS service to Floci, implementing AWS protocol-compatible handlers, writing integration or unit tests for Floci services, debugging AWS SDK compatibility issues, configuring storage modes, understanding Floci's architecture, working on the Floci codebase, or using Floci as a local AWS development environment. Always trigger this skill when the user mentions Floci, AWS emulator development, service implementation, AwsQueryController, AwsJson11Controller, StorageFactory, or any task involving the floci codebase — even if they don't explicitly say "Floci skill."
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. NOT for custom model training, Rekognition, or Comprehend.
Analyze AWS costs, find savings, manage budgets, evaluate Savings Plans and Reserved Instances, right-size EC2/Lambda/RDS/EBS with Compute Optimizer, look up service pricing, query CUR with Athena, detect cost anomalies, scope costs to billing views, and monitor Free Tier usage. Triggers on: AWS bill, cost analysis, reduce spend, savings plan, reserved instance, right-size, budget alert, cost optimization, pricing, free tier, cost anomaly, CUR, cost audit, billing view, billing view ARN.
Authors, deploys, and troubleshoots AWS infrastructure using CDK with TypeScript or Python. Covers best practices, stack architecture, and construct patterns. Always use when writing CDK constructs, bootstrapping environments, running cdk deploy/synth/diff, fixing CDK or CloudFormation errors, planning stack structure, importing existing resources, resolving drift, or refactoring stacks without resource replacement.
Author, validate, and troubleshoot AWS CloudFormation templates. Covers template authoring with secure defaults, pre-deployment validation (cfn-lint, cfn-guard, change sets), and root-cause diagnosis of failed stacks using CloudFormation events and CloudTrail correlation.
Deploys and operates containerized workloads on ECS, Fargate, and ECR. Covers task definitions, Fargate services, ECR repository setup and lifecycle policies, ECS Exec debugging, service scaling, deployment strategies, load balancer integration, and logging configuration. Use when deploying, debugging, or optimizing containers on AWS. ALSO USE for container deployment options (ECS vs ECS Express Mode), networking modes, health check troubleshooting, OOM errors, secrets injection, blue/green deployments, ECR image management, and App Runner sunset guidance and migration. NOT for Kubernetes, EKS, or CI/CD pipelines.