floci-sample

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.

Verified corrections for IAM behaviors that AI agents frequently get wrong — policy evaluation edge cases, trust policy gotchas, STS session limits, Organizations quirks, and SAML/MFA specifics. Use alongside documentation when working with IAM roles, policies, STS, or Organizations. Do NOT use for non-IAM authorization like Cognito user-pool policies or app-level RBAC.

Guides use of AWS messaging and streaming services. Covers Amazon SQS, Amazon SNS, Amazon EventBridge, Amazon MQ, Amazon Kinesis Data Streams, Amazon Data Firehose, Amazon Managed Service for Apache Flink, and Amazon Managed Streaming for Apache Kafka (MSK). Use when implementing messaging and streaming patterns.

Builds, configures, debugs, and optimizes AWS observability using CloudWatch (Logs Insights, Metrics, Alarms, Dashboards, EMF), X-Ray, CloudTrail, and ADOT. Covers Log Insights query syntax (fields, filter, stats, parse, pattern, join, subqueries), alarm configuration (metric, composite, anomaly detection, missing data treatment), dashboard design, custom metrics (PutMetricData, EMF, metric filters), X-Ray tracing (ADOT, sampling rules, annotations vs metadata), ADOT collector config, and CloudTrail auditing. Use when the user mentions CloudWatch, Log Insights, alarms, INSUFFICIENT_DATA, dashboards, custom metrics, EMF, X-Ray, traces, sampling, CloudTrail, who deleted, ADOT, OpenTelemetry, observability, monitoring, synthetics, canaries, or troubleshooting alarm behavior. Do NOT use for application logging setup, container log drivers, or security threat detection.

Builds, deploys, manages, debugs, configures, and optimizes serverless applications on AWS using Lambda, API Gateway, Step Functions, EventBridge, and SAM/CDK. Covers cold starts, CORS debugging, event source mappings, troubleshooting, concurrency, SnapStart, Powertools, function URLs, EventBridge Scheduler, Lambda layers, Durable Functions, durable execution, checkpoint-and-replay, and production readiness. Use when the user mentions Lambda, API Gateway, Step Functions, SAM templates, CDK serverless stacks, DynamoDB stream triggers, SQS event sources, cold starts, timeouts, 502/504 errors, throttling, concurrency, CORS, Powertools, Durable Functions, durable execution, checkpoint-and-replay, or any event-driven architecture on AWS, even if they don't say "serverless." Do NOT use for EC2, ECS/Fargate containers, or Amplify hosting.

AWS Well-Architected Framework（6つの柱）に基づいてAWSシステムを設計・構築・テスト・リファクタリング・レビューする際に、 厳格なベストプラクティス準拠チェックと改善提案を提供する専門スキル。 AWSを使ったシステム開発のあらゆる場面で積極的に使用すること。 ユーザーがAWSシステムの設計・実装・インフラ構成・CDK/CloudFormationテンプレート・Lambda関数・API Gateway設計・ DynamoDB設計・セキュリティポリシー・コスト試算・アーキテクチャレビュー・コードレビューなど AWSに関するいかなるタスクについて言及した場合は必ずこのスキルを参照してWell-Architected原則への準拠を確認すること。 "設計してほしい"・"実装してほしい"・"レビューしてほしい"・"最適化したい"・"CDK"・"Lambda"・"DynamoDB"・ "API Gateway"・"S3"・"CloudFront"・"ECS"・"Fargate"・"Bedrock"・"Cognito"・"IAM"などの キーワードが出た場合は必ずこのスキルを適用すること。

CDK TypeScript スタックファイルを読み取り、誰にでも伝わるAWS構成図をdraw.io形式で自動生成するスキル。 「CDKスタックを図にしたい」「AWS構成を可視化したい」「draw.ioの構成図を作りたい」「インフラの図を書いて」 「アーキテクチャ図が欲しい」「CDKコードを可視化して」など、CDK/インフラ/構成図に関する要望が出たら必ずこのスキルを使うこと。 CloudFormationテンプレートやCDKコードからAWS構成図を生成する場合も同様に使用すること。

Configures VPC endpoints (interface and gateway) for private AWS service access using AWS PrivateLink. Use when setting up secure private connectivity to S3, DynamoDB, and other AWS services without internet gateway, NAT device, or public IP addresses. Covers endpoint creation, security groups, route tables, and DNS configuration.

Connects an existing AWS Lambda function to Amazon API Gateway by creating a REST or HTTP API with resource/method setup, Lambda proxy integration, permissions, and deployment. Always use this skill when connecting Lambda to API Gateway — it handles CORS, throttling, access logging, and production security hardening that are easy to miss.

Connects an AWS Lambda function to DynamoDB with IAM roles, stream event source mapping, and read/write permissions. Use when setting up Lambda-DynamoDB integration, processing DynamoDB stream events, or deploying serverless event-driven architectures.

Create and troubleshoot AWS Glue connections to JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS), Redshift, Snowflake, and BigQuery. Gathers connection hints from user, discovers existing connections and RDS/Redshift candidates, registers credentials in Secrets Manager or IAM DB auth, configures VPC, and tests. Triggers on: connect to database, set up Glue connection, register data source, connect to Snowflake/BigQuery/RDS, connection timeout, test connection, troubleshoot connection. Do NOT use for moving data (use ingesting-into-data-lake), creating tables (use creating-data-lake-table), queries (use querying-data-lake), catalog exploration (use exploring-data-catalog), or SaaS (Salesforce, ServiceNow, SAP, MongoDB, Kafka).

Establishes VPC peering connections between two VPCs for direct private network connectivity. Always use this skill when creating or managing VPC peering — it validates CIDR overlap, updates all route tables in both VPCs, configures DNS resolution, and provides security group guidance that are critical for correct connectivity.

会話データから話者認識・感情読み取り・5W1H（いつ・どこで・誰が・何を・なぜ・どのように）抽出を行うプロダクトの設計・開発・レビューを包括的に支援するスキル。 **必ずこのスキルを使うべきシーン（1%でも当てはまれば即起動）：** - 「会話を解析したい」「誰が話しているか特定したい」「感情を読み取りたい」と言われたとき - 話者分離（Speaker Diarization）・話者認識（Speaker Identification）の実装を求められたとき - Emotion Recognition in Conversation (ERC)・感情推定・感情分析を実装するとき - 議事録生成・会議要約・会話ログ構造化など会話インテリジェンス全般 - 「誰がいつ何を話したか」「発言者は誰か」「どんな感情で話しているか」を抽出するシステム - 音声・テキスト・映像など複数モダリティを組み合わせた会話解析 - コールセンター・議事録・インタビュー・多人数会議・オンライン授業など会話データを扱う全シーン - 会話解析プロダクトのアーキテクチャ設計・コードレビュー・品質改善

Creates an API Gateway stage with CloudWatch logging, X-Ray tracing, throttling, WAF integration, and IAM roles following AWS best practices. Use when deploying a REST API to different environments such as dev, test, or production.

Creates and manages secrets in AWS Secrets Manager following security best practices. Always use this skill when creating secrets — it sets up dedicated KMS encryption keys, automatic rotation, least-privilege IAM policies, CloudTrail auditing, and lifecycle management that are essential for production-grade secret handling.

Debugs AWS Lambda function timeout failures by systematically analyzing function configuration, CloudWatch logs and metrics, VPC/networking, cold starts, memory constraints, and downstream dependencies to identify root causes with actionable fixes. Use when a Lambda function is timing out or approaching its timeout limit.

Use when user requests diagrams, flowcharts, architecture charts, or visualizations — including AWS architecture diagrams, cloud system diagrams, and infrastructure diagrams. Also use proactively when explaining systems with 3+ components, complex data flows, or relationships that benefit from visual representation. For AWS diagrams, always produces Dojo-quality output with official AWS service icons, correct category colors, and proper VPC/subnet/AZ groupings. Generates .drawio XML files and exports to PNG/SVG/PDF locally using the native draw.io desktop CLI.

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."

Marp形式プレゼンテーションの専門レビュー・評価・改善スキル。 10軸スコアリング（100点満点）で品質を定量評価し、具体的な改善コード付きで提案する。 Use when the user asks to: - Review, evaluate, or critique a Marp presentation / プレゼンをレビュー / 評価 / 添削 - Improve, polish, or upgrade existing slides / スライドを改善 / ブラッシュアップ - Check slide quality, score slides, or audit a deck / スライドの品質チェック / 採点 - "このプレゼンどう？" "スライドを見てほしい" "プレゼン資料のフィードバック" Reads .md files with Marp frontmatter, scores across 10 dimensions, and outputs a detailed review report with concrete before/after code improvements. Works as a companion to the marp-slides skill (generation → review → improvement cycle).

Create professional, visually excellent presentation slides in Marp Markdown format. Use this skill when the user asks to: - Create a presentation, slides, deck, slideshow, or プレゼン / スライド - Write or generate slides about a specific topic - Make a Marp .md file for presenting Produces complete, ready-to-render .md files with embedded custom CSS theme, narrative structure, and polished visual design. Supports Japanese and English content.

プレゼンテーション・コーチングスキル。スライド作成・構成・改善を支援する。 ユーザーが「プレゼンを作りたい」「スライドを改善したい」「発表資料を整理したい」「提案書を作る」「報告資料を作成する」「ピッチデッキを作りたい」と言ったとき、または既存のスライドや資料についてフィードバックを求めているとき、必ずこのスキルを使うこと。 プレゼン・スライド・資料作成に関するあらゆる要求に積極的に適用する。

リポジトリの構造・技術スタック・機能一覧・セットアップ手順を動的に解析し、 包括的なドキュメントを自動生成するスキル。言語・フレームワーク問わず汎用的に動作する。 Use this skill whenever the user asks to: - Explain a repository / リポジトリの説明 / リポジトリの概要 - Generate a README / README生成 / README作成 - Understand project structure / プロジェクト構成を教えて / 構造を説明して - Learn how to run a project / 使い方を教えて / 動かし方 / セットアップ方法 - Get a repo overview / repo overview / explain this repo / what does this repo do - List features / 機能一覧 / このプロジェクトは何ができる？ - Onboard to a new codebase / コードベースのキャッチアップ / 新しいリポジトリに入った - "このリポジトリ何？" "プロジェクトの全体像" "how to run this project" - "コードの全体を把握したい" "ドキュメントを整備して" "技術スタックを知りたい" This skill is especially useful when joining a new project, onboarding team members, or when a repository lacks proper documentation. It works with ANY repository regardless of programming language, framework, or project type.

Configures Amazon Route 53 to route traffic to a CloudFront distribution using a custom domain. Use when setting up DNS alias records, alternate domain names (CNAMEs), ACM certificates for HTTPS, and IPv6 support for CloudFront.

Create and secure S3 buckets following AWS best practices for access control, encryption, monitoring, and remediation of misconfigurations. Use when the user wants to secure a new bucket, audit an existing bucket, fix a security finding, configure encryption, or enable logging and monitoring. Do NOT use for general S3 data operations, S3 Tables setup, or discovering existing data assets.

Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks.

Use when searching academic papers, looking up citations, finding authors, or getting paper recommendations using the Semantic Scholar API. Triggers on queries about research papers, academic search, citation analysis, or literature discovery.