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Terraform infrastructure-as-code patterns for AWS and Azure provisioning. Use when creating or modifying .tf files, writing Terraform modules, managing remote state (S3, Azure Storage), working with terraform commands (init, plan, apply, destroy), configuring providers (AWS, Azure, Google Cloud), or implementing infrastructure best practices like module design, workspace strategies, and state locking.

Maintain sloc-guard project documentation. Use when user completes a feature and asks to update docs.

Technical research methodology with YAGNI/KISS/DRY principles. Phases: scope definition, information gathering, analysis, synthesis, recommendation. Capabilities: technology evaluation, architecture analysis, best practices research, trade-off assessment, solution design. Actions: research, analyze, evaluate, compare, recommend technical solutions. Keywords: research, technology evaluation, best practices, architecture analysis, trade-offs, scalability, security, maintainability, YAGNI, KISS, DRY, technical analysis, solution design, competitive analysis, feasibility study. Use when: researching technologies, evaluating architectures, analyzing best practices, comparing solutions, assessing technical trade-offs, planning scalable/secure systems.

Use when writing tests, debugging test failures, mocking dependencies, or using fake timers. Covers Vitest patterns, mock factories, and promise rejection handling.

Google Gemini CLI orchestration for AI-assisted development. Capabilities: second opinion/cross-validation, real-time web search (Google Search), codebase architecture analysis, parallel code generation, code review from different perspective. Actions: query, search, analyze, generate, review with Gemini. Keywords: Gemini CLI, second opinion, cross-validation, Google Search, web research, current information, parallel AI, code review, architecture analysis, gemini prompt, AI comparison, real-time search, alternative perspective, code generation. Use when: needing second AI opinion, searching current web information, analyzing codebase architecture, generating code in parallel, getting alternative code review, researching current events/docs.

Use when making architecture decisions, creating ADRs, designing system components, evaluating technology choices, or planning technical implementations. Invoked for system design, scalability analysis, and platform decisions.

Code comment guidelines based on industry best practices. Use when reviewing code, writing new code, or when asked about comment quality. Applies to all languages but specializes in TypeScript/JavaScript. Enforces "JSDoc for public APIs only, no redundant comments" principle. Automatically suggests comment additions, removals, or refactoring alternatives.

MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.

Analyze checkpoint tests and suggest missing edge cases. Use after writing tests or when reviewing test coverage. Invoke with /edge-cases <problem> <checkpoint>.

Use when parsing "All Needed Context" sections from PRD files. Extracts code files, docs, examples, gotchas, and external systems into structured JSON format. Invoked by /flow:implement, /flow:generate-prp, and /flow:validate.

Analyze checkpoint tests and suggest missing edge cases. Use after writing tests or when reviewing test coverage. Invoke with /edge-cases <problem> <checkpoint>.

Use this skill at the beginning of any session or when needing to understand available project documentation. Provides just-in-time context by scanning YAML frontmatter from all markdown files in the docs/ directory without loading full content.

Iteratively craft an AUTHOR_VOICE.md document that captures your unique writing style for AI replication. Use when creating a voice profile via /craft-voice. Interactive multi-choice workflow with feedback cycles.

Systematic code refactoring following Martin Fowler's catalog. Methodologies: characterization tests, Red-Green-Refactor, incremental transformation. Capabilities: SOLID compliance, DRY cleanup, code smell detection, complexity reduction, legacy modernization, design patterns, functional programming patterns. Actions: refactor, extract, inline, rename, move, simplify code. Keywords: refactor, SOLID, DRY, code smell, complexity, extract method, inline, rename, move, clean code, technical debt, legacy code, design pattern, characterization test, Red-Green-Refactor, functional programming, higher-order function, immutability, pure function, composition, currying, side effects. Use when: improving code quality, reducing technical debt, applying SOLID principles, fixing DRY violations, removing code smells, modernizing legacy code, applying design patterns.

MarkdownファイルをPowerPointプレゼンテーション（PPTX）に変換するSkill。 「Markdownをスライドに変換して」「プレゼン資料を作って」「PPTXを生成して」 などのリクエストで自動発火する。python-pptxライブラリを使用。

Write clear, emotionally resonant, and well-structured content that readers remember and act upon. Use when writing or editing any text—Twitter posts, articles, documentation, emails, comments, updates—for maximum clarity, engagement, and impact.

Use this skill when working with CPython documentation in the Doc/ tree, including reStructuredText (.rst) files, adding versionadded/versionchanged markers, creating Misc/NEWS.d entries for bug fixes or features, running documentation validation (make -C Doc check), or building HTML docs.

将 PDF 文件转换为结构化的中文 Markdown 文本。只在用户明确要求“把 PDF 转成 Markdown/MD/文档”时使用本技能。

This skill should be used when writing, reviewing, or improving RSpec tests for Ruby on Rails applications. Use this skill for all testing tasks including model specs, controller specs, system specs, component specs, service specs, and integration tests. The skill provides comprehensive RSpec best practices from Better Specs and thoughtbot guides.

Orchestrate fixing issues found by /review. Handles issue discovery, user confirmation, prioritized execution, and progress tracking. Works with review output from any category (bugs, maintainability, types, docs, coverage, claude-md).