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概要と使いどころ
How to add a page to the tdmcp VitePress docs site so it builds, gets a clean URL, and lands in the right nav — including the repo's partial-translation convention (only the artist guide is EN+PT; reference/legal pages are English). Use when authoring the privacy policy or any new docs page for tdmcp.
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。
CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.
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。
Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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 creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.
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。
First-run guided setup for a fresh gAIOS clone. Interviews the user (identity, role, priorities, voice, connections, team, pain, guardrails) and fills the templates — CLAUDE.md, context/, references/voice.md, connections.md — then introduces the WAT / wiki / workflows / experiments features. Trigger on "/setup", "set me up", "get started", "onboard me", or a fresh clone where CLAUDE.md still has {{placeholders}}.
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, repair, explain, and verify private Obsidian synchronization across Windows, macOS, GitHub, and mobile devices. 配置、修复、解释并验证 Windows、macOS、GitHub 与移动设备之间的 Obsidian 私有同步。Use for private vault repositories, Windows edit-event sync, macOS Obsidian Git sync, mobile setup, GitHub token/key guidance, Pull/Commit/Push workflow explanation, device-setting isolation, duplicate-note diagnosis, accidental deletion recovery, multi-device sync strategy, failed pushes, and end-to-end checks. 用于私有笔记仓库、Windows 编辑事件同步、macOS Obsidian Git 同步、移动端配置、GitHub Token/Key 指导、Pull/Commit/Push 工作流解释、设备设置隔离、重复笔记诊断、误删恢复、多端同步策略、推送失败和端到端检查。
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。
Guides intentional Nothing-inspired UI and design-system work with typography, spacing, hierarchy, components, and platform-specific execution. Use when the user explicitly asks for Nothing style, Nothing design, or `/nothing-design`, not for generic UI or design tasks.
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。
Comprehensive guide for building robust, secure, and efficient CI/CD pipelines using GitHub Actions. Use when the task involves `creating or editing GitHub Actions workflows`, `.github/workflows/*.yml`, `CI/CD pipelines`, `GitHub Actions best practices`, or `workflow optimization`.
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 and improve web accessibility following WCAG 2.1 guidelines. Use when the task involves `improve accessibility`, `a11y audit`, `WCAG compliance`, `screen reader support`, `keyboard navigation`, or `make accessible`.
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 the user wants Codex to build, refine, test, or validate a CLI-Anything harness for a GUI application or source repository. Adapts the CLI-Anything methodology to Codex without changing the generated Python harness format.
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 for requirements interviews. Triggers: interview, ambiguity, contradiction scan, ask me questions, I phase, 인터뷰.
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 conducting Torres-style story-based interviews with the people whose experience you're researching, with bias mitigation and a JTBD lens.
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。
GIST planning workflow. Structure goals into ideas, steps, and tasks using Gilad's evidence-guided framework.
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。
Simulate rigorous, fair peer review on a paper — in two modes. (A) Red-team YOUR OWN draft before submission to predict the reviews you'll get and get a fix list. (B) Review SOMEONE ELSE'S paper when you're an assigned reviewer or helping your advisor — produce a fair, venue-formatted, submission-ready review. Use whenever the user gives a paper (PDF, .tex, .md, arXiv link, or pasted text) and wants to predict reviews, find weaknesses before reviewers do, stress-test a submission, OR write a real review of another paper. Grounded in official NeurIPS/ICLR/ACL reviewer guidelines; every criticism pinned to a location, and checked against ACL's H1–H17 list of illegitimate critiques. 两种模式:审自己的稿(投稿前红队)/ 审别人的稿(当审稿人或帮导师),按会议官方标准评,绝不脑补、绝不发不正当批评。
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。
Apply MCAF feature-spec guidance to create or update a feature spec under `docs/Features/` with business rules, user flows, system behaviour, verification, and Definition of Done. Use when the user asks for a feature spec, executable requirements, acceptance criteria, behaviour documentation, or a pre-implementation plan for non-trivial behaviour changes.
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。
Apply MCAF developer-experience guidance for onboarding, F5 contract, cross-platform tasks, local inner loop, and reproducible setup. Use when the repo is hard to run, debug, test, or onboard into.
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。
Apply MCAF UI/UX guidance for design systems, accessibility, front-end technology selection, and design-to-development collaboration. Use when bootstrapping a UI project, choosing front-end stack, or tightening design and accessibility practices.
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。
Apply MCAF agile-delivery guidance for backlog quality, roles, ceremonies, and engineering feedback. Use when defining how the team plans, tracks work, and turns feedback into durable improvements.
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。
Apply MCAF human-review-planning guidance for a large AI-generated code drop by reading the target area, tracing the natural user and system flows, identifying the riskiest boundaries, and prioritizing the files a human should inspect first. Use when the codebase is too large to review line-by-line and you need a practical review sequence plus a prioritized file list.
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。
Create or refine durable engineering documentation: docs structure, navigation, source-of-truth placement, and writing quality. Use when a repo’s docs are missing, stale, duplicated, or hard to navigate, or when adding new durable engineering guidance.
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。
Apply MCAF source-control guidance for repository structure, branch naming, merge strategy, commit hygiene, and secrets-in-git discipline. Use when bootstrapping a repo, tightening PR flow, or documenting branch and release policy.
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。
Apply MCAF non-functional-requirements guidance to capture or refine explicit quality attributes such as accessibility, reliability, scalability, maintainability, performance, and compliance. Use when a feature or architecture change needs explicit quality attributes and trade-offs.
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。
Apply MCAF ML/AI delivery guidance for data exploration, feasibility, experimentation, testing, responsible AI, and operating ML systems. Use when the repo includes model training, inference, data science workflows, or ML-specific delivery 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。
Guides developers through a human-supervised PDCA framework for AI code generation. Applies analysis, TDD, validation, and retrospection. Activates for sessions requiring systematic quality control.
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。