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概要と使いどころ
从整个工作区出发，系统性地重组认知结构并整理全局文档归属。适用于首次建立认知结构、或积累了大量散落文档需要批量归档时。基于三大闭环框架（Loop1 Skill体系 / Loop2 思维体系 / Loop3 场景投射）做全工作区分类路由。触发词：「系统整理」「重组认知结构」「从文档构建认知结构」「整合文档」「全量梳理」「认知结构乱了」「全工作区整理」「文档归属梳理」「如何加入认知结构」「怎么加入认知结构」「按规范加入」「未更新的文档怎么处理」「这些文档要怎么整理」「有没有关于X的已有文档」。注意：若用户仅询问流程而非执行重组，执行 Step 0.5（检查分类清单现状）后，先向用户展示已有文档状态和分类建议，再确认是否执行完整重组。
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。
Propose a new OpenSpec change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation. Also use when the user says "openspec propose" or "opsx propose".
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。
Propose a new change with all artifacts generated in one step. Use when the user wants to quickly describe what they want to build and get a complete proposal with design, specs, and tasks ready for implementation.
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 excellent web forms: UX patterns, validation, accessibility, multi-step flows, and file uploads. Use for any form beyond trivial inputs.
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 agents on OpenAI's platform patterns — assistants-style threads, function calling, structured outputs, and multi-step tool workflows. Use when working with OpenAI models as the agent engine.
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 and build LLM agents: ReAct loops, tool schemas, planning, memory, guardrails, evals, and human-in-the-loop. Use when building autonomous multi-step AI systems.
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 LLM applications with chain-style orchestration frameworks — prompts, chains, tool-calling agents, memory, and retrieval pipelines. Use when structuring multi-step LLM programs, adding tools to a model, or composing RAG systems in code.
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。
Set up and operate a Shopify store with Shopify's official MCP server (the installed `shopify` command, NOT the npm Shopify CLI). Use whenever someone wants to sell online, start an online store or business, try Shopify, or manage a Shopify store — even if they do not say "Shopify": "I want to sell candles online", "help me start an online business", "open my first store", "add products", "check my orders", "set inventory", "make a discount", "show my sales", "how did my Shopify Email campaigns do". Before connection it can show relevant mock.shop sample catalogs, suggest business names, check domains, search shopify.dev, and validate GraphQL. The connect flow can create an account and store for a new user. Do the work here rather than only listing setup steps. Keywords: Shopify MCP, ecommerce, sample products, demo store, starter catalog, ShopifyQL, first store, create product.
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。
The user's synced Google Health Connect data from their Android device: daily metrics (steps, distance, calories, heart rate, HRV, VO2max), sleep sessions (stages, quality, efficiency), and workouts.
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。
The user's synced Apple Health (HealthKit) data: daily metrics (steps, distance, calories, heart rate, HRV, VO2max), sleep sessions (stages, quality, efficiency), and workouts.
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。
Conduct a complete feature workflow in one skill — brainstorm, plan, TDD implementation, self-review, delivery summary — with hard gates between stages: no stage starts until the prior stage's artifact exists on disk (brainstorm note, plan doc, green tests per step)..
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。
Generate an ASC 606 / IFRS 15 revenue recognition engine for SaaS — the five-step model (identify contract, identify performance obligations, determine transaction price, allocate to performance obligations, recognize as POs are satisfied) applied to subscription contracts.
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。
Analyze game code for performance bottlenecks including draw call batching and overdraw, shader complexity and LOD strategy, per-frame GC allocation pressure, object pooling gaps, physics timestep and collision matrix tuning, spatial partitioning for entity queries.
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。
Write multi-email nurture sequences for lead-gen, onboarding, re-engagement, sales, and lifecycle marketing using the Hook Model (Nir Eyal) to architect the sequence arc and PAS (Problem-Agitate-Solution) to structure each email body. Use when the user asks for an email sequence, drip campaign, nurture flow, onboarding emails, re-engagement campaign, "write 5 emails for X", welcome series, or any multi-step email program. Reads brand voice and ICP from knowledge/. For a single cold outreach email, see pr-pitch-writer. For the newsletter, see newsletter-writer. For testing subject lines, see ab-copy-writer.
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。
Write a clear, reviewable audit workpaper documenting procedures, evidence, and conclusions. Use when an auditor says "write a workpaper", "document this audit procedure", "tick and tie this", "I need to document my testing", "substantive testing workpaper", "controls testing documentation", "audit evidence memo", "prepare the workpaper for this balance", "document the audit steps I performed", or needs to capture any audit work in a format that supports review and sign-off. Also trigger when someone has completed audit testing and needs to write it up even if they don't use the word "workpaper".
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 you have a spec or requirements for a multi-step task, before touching code
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。
Smallest personal narrated-explainer-video pipeline (spoken narration over visuals, not an audio podcast), fully tool-agnostic and autonomous by default — topic → research ∥ asset collection → script → TTS → video → 4K render ∥ publish info + cover. The skill defines the pipeline logic and self-verified checkpoints; any TTS backend and any video tool (Remotion, HyperFrames, CapCut, ...) work, and how much human oversight to apply is set by the working project's AGENTS.md/CLAUDE.md, not here. Use when the user wants a quick personal narrated video with minimal steps, whether or not they name the tool stack. Do NOT trigger for audio-only podcasts, written episodic content, or heavy multi-format production.
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。
Canonical patterns for caching in Yuzu CI workflows. Two snippets — one for ephemeral GHA-hosted runners (split actions/cache/restore + actions/cache/save, never `save-always: true`) and one for self-hosted runners (local filesystem cache under `runner.tool_cache`, no GHA cache round-trip). Use when adding a new vcpkg/ccache/dependency cache step to any workflow under `.github/workflows/`, or when reviewing a PR that touches `actions/cache@`.
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。
Run the Yuzu pre-commit/pre-push test pipeline. Compiles HEAD, stands up the previous release, upgrades it, runs the full standard test surface, records every result + sub-step timing into a durable SQLite test-runs DB. Use when the user says "/test" or asks to run the full test pipeline before commit.
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。
Migrates Android applications from the old, legacy Google Mobile Ads (GMA) SDK (com.google.android.gms:play-services-ads) to the new GMA Next-Gen SDK (com.google.android.libraries.ads.mobile.sdk:ads-mobile-sdk). Provides comprehensive mapping tables for imports, classes, and method signatures to help determine migration steps. Use when migrating an existing Android codebase from the old, legacy GMA SDK to GMA Next-Gen SDK.
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。
Creates Cloud Storage (Google Cloud Storage, or GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.
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 a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.
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 agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).
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 client library installation and authentication setup steps for the Data Manager API. Use this skill when a user is getting started with the Data Manager API and needs to setup their local environment, install the client library, or setup access to the API. Don't use for implementing audience or event ingestion logic (use the data-manager-api-audience-ingestion or data-manager-api-event-ingestion skills 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。