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概要と使いどころ
Activate for changes to project positioning, release communication, community-facing artifacts, or breaking-change decisions in microsoft/apm. Triggers on README, MANIFESTO, PRD, CHANGELOG, release workflows, and issue templates.
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。
Coordinate Lark/Feishu CLI tasks from Codex. Use when a request involves Feishu/Lark docs, wiki, Drive files, Sheets, Base, Calendar, Minutes, IM, Mail, Tasks, Contacts, Slides, whiteboards, approvals, attendance, or when a Lark URL/token must be read, edited, summarized, routed, or turned into a real work artifact.
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。
Inspect GitHub pull requests, issues, workflow runs, and API data with the gh CLI. Use when the user wants repository facts from GitHub without opening the browser, especially for PR status, CI failures, issue lists, or structured JSON output.
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。
React composition patterns that scale. Use when refactoring components with boolean prop proliferation, building flexible component libraries, or designing reusable APIs. Triggers on tasks involving compound components, render props, context providers, or component architecture. Includes React 19 API 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。
Build, refactor, or review macOS menubar apps that use Tuist and SwiftUI. Use when creating or maintaining LSUIElement menubar utilities, defining Tuist targets/manifests, implementing model-client-store-view architecture, adding script-based launch flows, or validating reliable local build/run behavior without Xcode-first workflows.
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。
Implement, review, or improve SwiftUI features using the iOS 26+ Liquid Glass API. Use when asked to adopt Liquid Glass in new SwiftUI UI, refactor an existing feature to Liquid Glass, or review Liquid Glass usage for correctness, performance, and design alignment.
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。
Best practices and example-driven guidance for building SwiftUI views and components, including navigation hierarchies, custom view modifiers, and responsive layouts with stacks and grids. Use when creating or refactoring SwiftUI UI, designing tab architecture with TabView, composing screens with VStack/HStack, managing @State or @Binding, building declarative iOS interfaces, or needing component-specific patterns and examples.
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。
Review a git diff or explicit file scope for reuse, code quality, efficiency, clarity, and standards issues, then optionally apply safe Codex-driven fixes. Use when the user asks to "simplify code", "review changed code", "check for code reuse", "review code quality", "review efficiency", "simplify changes", "clean up code", "refactor changes", or "run simplify".
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。
Sample-size and statistical power calculations for planning studies. Use whenever someone asks "how many subjects/samples/replicates do I need", wants an a priori power analysis, a minimum detectable effect (MDE), a power curve, or needs to justify a sample size for a grant, IRB protocol, or pre-registration. Covers closed-form power for t-tests, ANOVA, proportions, correlations, chi-square, and regression, plus simulation-based (Monte Carlo) power for designs with no formula — logistic/Poisson regression, mixed models, cluster-randomized trials, survival, and interactions. Use this skill even when the request only mentions an effect size, alpha, or "80% power" without saying "power analysis" explicitly. For laying out the study (randomization, blocking, factorial/DOE, crossover, sequential designs) use experimental-design; for analyzing data already collected and reporting it use statistical-analysis.
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。
Design or revise a Marin experiment pipeline that binds reusable work into an artifact graph. Use for new workflow entrypoints, stage wiring, and pipeline placement decisions; use a narrower domain skill when it owns the launch.
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。
Define, validate, submit, or restart a Marin SkyRL experiment through its artifact main. Use for RL launch files, SkyRLRolePlan or SkyRLTopology changes, MarinSkyRL configuration, RL smoke tests, and requests to launch or relaunch RL on Iris.
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。
Search Experience Optimization (SXO), the bridge between SEO and UX/CRO. Audits the journey from the SERP click to the on-page goal: click-through factors (title, meta, rich results), then post-click signals that keep users and drive conversions: above-the-fold relevance and intent match, page speed / Core Web Vitals, readability, clear CTAs, mobile usability, and what causes pogo-sticking back to Google. Use when the user has decent rankings but poor CTR or poor on-page conversion, wants better dwell time / engagement, less bounce, or a page experience aligned with search intent. Trigger on: "SXO", "search experience optimization", "good rankings but low CTR", "high bounce rate from search", "pogo-sticking", "improve dwell time", "SEO and conversion", "ranking but not converting", "engagement signals", "make this page convert search traffic". For pure landing-page conversion in ads use /google-ads-landing; for content quality use /seo-page.
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。
Single-page SEO audit: content quality under Google's E-E-A-T framework and Helpful Content guidelines, on-page factors, search intent, technical signals and readability. Pulls GSC data for the page, crawls the live HTML, checks metadata, schema, internal linking and depth, and produces a scored report with fixes. Use whenever the user wants to analyze a specific page or URL, not the whole site. Trigger on: "analyze this page", "audit this URL", "how is this page doing", "evaluate my blog post", "check this landing page", "page SEO", "content quality check", "is this page good enough", "review this page's SEO", "what's wrong with this page", "how can I improve this page", "page analysis", "single page audit", "content audit for [URL]", or any request naming a specific URL/page for SEO evaluation. If the user provides a specific URL (not just a domain), this is likely the right skill; use /seo-analysis for full-site audits instead.
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。
Local SEO and Google Business Profile audit: diagnose why a business isn't ranking in the local pack / map results and produce a fix plan. Covers GBP completeness, NAP (name/address/phone) consistency across the site and citations, local pack and "near me" ranking factors, review velocity and responses, local landing pages, service-area pages, and LocalBusiness JSON-LD. Use whenever the user asks about local rankings, map results, Google Maps ranking, NAP consistency, store/branch pages, or multi-location SEO. Trigger on: "local SEO", "Google Business Profile", "GBP audit", "rank on Google Maps", "local pack", "map pack", "near me ranking", "NAP", "local citations", "my business isn't on the map", "why don't I show up on Google Maps", "store locator SEO", "multi-location SEO", "service area pages", or any location-based ranking question. For full-site (non-local) audits use /seo-analysis; for a single URL use /seo-page.
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。
Token-efficient code analysis via 5-layer stack (AST, Call Graph, CFG, DFG, PDG). 95% token savings.
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。
Test-driven development workflow with philosophy guide - plan → write tests → implement → validate
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。
AST-based code search and refactoring via ast-grep MCP
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。
Find unused functions and dead code in the codebase
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。
Build or evolve a complex agent-enabled Tutti workspace app repository. Use for Tutti apps with web/server/shared monorepos, @tutti-os/agent-acp-kit local agent runtimes, kit-owned TUTTI_CLI agent/composer discovery, dynamic agent catalogs, run-scoped MCP tool gateways, app-owned package builders, web-first debugging, i18n harnesses, and production package validation. For simple package creation or repair, use tutti-workspace-app-factory instead.
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。
工作流组合：当一个任务明显需要多件思想武器接力时，提供四种标准组合模式（新项目启动、复杂问题攻坚、方案迭代优化、阶段复盘），定义调用顺序、每步交接物和终止条件。触发信号包括从零启动、疑难攻坚、迭代优化、阶段复盘；单一 skill 就够用时不触发。 English: Workflow patterns. When a task clearly needs several skills in sequence, pick one of four standard patterns (project kickoff, hard-problem assault, iterative improvement, stage retrospective) that fix the order, the handoff artifact between steps, and the stop condition. Skip when a single skill suffices.
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。
求是方法论的入口与总原则。在每次新的顶层会话开始时加载一次，用「实事求是」约束全部判断，并只在明确适用时把任务路由到对应的方法论 skill；被派遣执行单一具体任务的子 agent 直接跳过。 English: Entry point and governing principle of the Qiushi methodology. Load once at the start of a top-level session to enforce "seek truth from facts" and route to a downstream skill only when it clearly helps. Delegated sub-agents on narrow tasks should skip it.
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。
Recon intake skill for first contact with a bare domain, URL, or IP address. Use to build an initial recon_profile and provide factual inputs for CVE lookup and attack-path routing.
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, compile, and validate site-specific WebMCP init scripts from a target URL and desired tool capability. Use when the user wants to author WebMCP tools for a website, produce a webmcp.init.js artifact, or test WebMCP registration and invocation through Stagehand.
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 asks to create or edit videos end-to-end (script→video, auto-cut/jumpcut, captions/subtitles, polishing for Shorts/Reels/TikTok). Current implemented backend: local FFmpeg (probe/render/jumpcut/burn-subtitles/polish). Planned/optional backends: Remotion (motion graphics templates), VectCutAPI (CapCut/剪映 timeline editing), and video-audio-mcp (MCP tool wrapper) when available. Produces a finished video artifact (MP4 by default) from assets + copy + a design/storyboard plan.
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。