dotfiles

日本語の技術文書・書籍原稿の文章規範。整形（markdown を前提とした段落・コードブロック・脚注・強調の使い分け）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

Use when writing or revising a design doc / ADR / 設計文書 that lives in the repo (docs/ 配下), and the draft reads like AI slop from session back-and-forth — 太字ラベルの乱用、演出語・英語造語、両論併記、説明の重複、一文ごとのインラインリンク — and must become the author's settled view that a first-time reviewer can follow.

計画・設計について、共通認識に達するまで徹底的に質問を投げかけてもらう。 設計ツリーを枝分かれの先までたどり、決定事項間の依存関係を順番に解決する。 Use when: "grill me", "質問攻めにして", "計画を詰めて", "設計を詰めて", "認識を合わせたい", "徹底的に質問して" Do NOT use for: 既に合意済みの計画の実装、単純な調査タスク

実装プラン/設計ドキュメントを Codex でクロスチェックして磨き込む（discovery→トリアージ→検証→修正の1サイクル）。 指摘のトリアージと検証を経てプランを Edit で修正し、residual-risk を明示して締める。 基本は discovery 1パス、修正が大きいときだけ fix-verification を条件付きで反復。 Use when: "プランをcodexでレビュー", "プランをブラッシュアップ", "設計を磨き込む", "プランを詰めて", "plan refine", "プランの抜け漏れを潰して" Do NOT use for: コード差分のレビュー、単発の質問、合意済みプランの実装

Interact with the Gemini Enterprise Agent Platform Skill Registry to create and search for available skills. Use this skill to enable agents to register functionality or discover new capabilities.

Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations.

Manages datasets, tables, and jobs in BigQuery, and integrates with BigQuery ML and Gemini for advanced data analytics and AI-driven insights. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources, or leverage BigQuery's built-in ML capabilities. Also use when performing data analysis, ingesting data into BigQuery, or developing AI applications on BigQuery.

Manages Cloud Run services, jobs, and worker pools. Use when you need to deploy applications responding to HTTP requests (services), run event-triggered or scheduled tasks (jobs), or handle always-on pull-based background processing (worker pools).

This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.

Use this skill whenever you are working on a project that uses Firebase products or services, especially for mobile or web apps.

Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.

Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.

Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.

Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs, NAT, firewall, or threat logs, querying latency and throughput metrics, or running Connectivity Tests for path diagnostics.

Provides expert guidance on authenticating and authorizing to Google Cloud services and APIs, covering human users, service identities, Application Default Credentials (ADC), and best practices for secure access.

Guidance for a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource.

Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.

Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.

Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.

Generates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.

Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

plan mode で作成したプランファイルを Codex にレビューさせ、設計漏れ・リスク・代替案・過剰設計を洗い出す。実装着手前のクロスチェックに使う。

PRのレビューコメントをスコアリングし、対応すべきかトリアージする。 コメントを修正する前に、技術的妥当性・影響度・false positive度を評価し、対応優先度を判定する。 Use when: "レビューコメントをスコアリング", "PRコメントをスコアリング", "review comment scoring", "レビューコメントの対応", "PRコメント対応", "レビュー対応して" Do NOT use for: 自分でコードレビューを行う場合（code-review スキルを使う）

Review a Claude Code skill against official best practices. Use when the user asks to review, lint, or check a skill quality.

Goバックエンドの実装計画を周辺実装まで読み込んで精査するための深掘りレビュー手順。計画レビュー・設計妥当性チェック時に使う。

作業中のセッション内容から「スキルに昇華できるルール・手順・知見」を抽出し、スキル候補を提案する。ユーザーが「スキルとしてまとめて」「提案して」「このセッションからスキル化できるものある？」などと依頼したときに使う。

AGENTS.md の整理・リファクタリングに特化。ユーザーが「agents.md を整理して」「AGENTS.md を更新して」などと言ったときに使う。各セッションで得た学びを汎用ルールとして AGENTS.md に反映するための提案を作成し、必ず提案から入って合意後に編集する。

Review GitHub pull requests using the gh CLI. Use when a user asks for a PR review, architectural feedback, or wants a structured checklist and summary based on gh pr view/diff/comments or gh api pull request comments.

Create or refine implementation plan files while consulting on design policy. Use when a user wants a plan drafted, then wants to identify design decision points, evaluate options, and finalize decisions before handoff to another session.