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概要と使いどころ
Garnish — Craft CMS's built-in JavaScript UI toolkit for the control panel. ALWAYS load when writing, editing, or reviewing JavaScript that runs in the Craft CP — plugin CP assets, custom field type JS, element index JS, CP webpack config, or code importing garnishjs / referencing window.Garnish. Also for CP accessibility, keyboard interactions, drag-sort, and CP JS memory issues.
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。
Startup Launch Day Playbook — Hour-by-hour execution checklist for your big launch day. Covers timezone timing, channel sequencing, real-time crisis management, and post-launch momentum. By @WeiYipei.
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。
竞品深度扫描与早期付费客户证据研究；输出行业画像假设和可验收需求交接。批量抓取对手落地页（title/h1/intro/pricing）、定价页、博客 top 10、 变更历史（Wayback）。底层调 actionbook（并发 30 tab + 省 90% token）。 当用户说"分析对手"、"看看竞品在做啥"、"找对标"、"扫一下 top 10"时调用。
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。
Reviews React Router code for proper data loading, mutations, error handling, and navigation patterns. Use when reviewing React Router v6.4+ code, loaders, actions, or navigation logic.
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。
Reviews sqlx database code for compile-time query checking, connection pool management, migration patterns, and PostgreSQL-specific usage. Use when reviewing Rust code that uses sqlx, database queries, connection pools, or migrations. Covers offline mode, type mapping, and transaction patterns.
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。
Data persistence patterns in Go covering raw SQL with sqlx/pgx, ORMs like Ent and GORM, connection pooling, migrations with golang-migrate, and transaction management. Use when implementing database access, designing repositories, or managing schema migrations.
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 Swift animation code using Apple's latest frameworks — SwiftUI animations, Core Animation, and UIKit. Prefer first-party APIs over third-party libraries. Use when implementing iOS animations, writing animation code, building transitions, creating gesture-driven interactions, or converting animation specs/designs into working Swift code. Covers iOS 18 through iOS 26 APIs including KeyframeAnimator, PhaseAnimator, custom Transition protocol, zoom navigation transitions, matchedGeometryEffect, symbol effects, mesh gradients, and SwiftUI-UIKit animation bridging.
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。
Reviews PostgreSQL code for indexing strategies, JSONB operations, connection pooling, and transaction safety. Use when reviewing SQL queries, database schemas, JSONB usage, or connection management.
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 plan iOS animations with structured specs covering transitions, micro-interactions, gesture-driven motion, and loading states. Use when the user asks to plan, design, or spec out animations for an iOS app — including screen transitions, navigation animations, interactive gestures, onboarding flows, or any motion design work. Also use when the user wants animation recommendations or wants to decide between animation approaches before writing 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。
Detects common LLM coding agent artifacts across four categories (tests, dead code, abstraction, style) over the project or changed files — using parallel subagents when the agent supports them, otherwise four sequential passes. Scans files changed since main by default; use --all for full-project scan. Triggers on LLM cruft cleanup, agent-generated code review, dead code sweeps, test-quality passes, or when the user asks to scan the whole repo.
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 PydanticAI agents using TestModel, FunctionModel, VCR cassettes, and inline snapshots. Use when writing unit tests, mocking LLM responses, or recording API interactions.
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。
Register and implement PydanticAI tools with proper context handling, type annotations, and docstrings. Use when adding tool capabilities to agents, implementing function calling, or creating agent actions.
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 need to mine a conversation, session transcript, or design discussion for architectural decisions before writing ADRs. Identifies problem-solution pairs, trade-off debates, technology choices, and explicit "[ADR]" tags. Triggers on "what decisions did we make", "extract decisions from this chat", "find the choices in our discussion", or "summarize architectural decisions". Also useful after long planning sessions to capture decisions that were made implicitly. Does NOT write ADR documents — use adr-writing or write-adr for that.
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 writing or formatting an ADR document using the MADR template, applying Definition of Done (E.C.A.D.R.) criteria, or verifying ADR completeness. Triggers on "write the ADR", "format as MADR", "check ADR quality", "mark gaps in ADR". Also triggers when a decision has been extracted and needs to become a document. Does NOT extract decisions from conversations (use adr-decision-extraction) or orchestrate the full extract-confirm-write workflow (use write-adr).
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 reviewing, critiquing, or stress-testing an existing strategy document. Evaluates seven dimensions — diagnosis quality, guiding policy strength, action coherence, assumption exposure, falsifiability — with optional 7S, Five Forces, Balanced Scorecard, and Hoshin Kanri lenses. Triggers on: review my strategy, poke holes in this plan, what's weak here, strategy audit, red team this. Does NOT build strategy (use strategy-interview) or brainstorm project ideas (use brainstorm-beagle).
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。
Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent-introduced cruft.
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。
Repo-wide structural-maintainability review — code-judo restructurings, 1k-line file guard, anti-spaghetti branching, canonical-layer enforcement, anti-magic abstractions, explicit type/boundary 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。
Diagnose Kolu client-side performance issues (memory leaks, high GPU, slow interactions) using chrome-devtools MCP + the Debug → Diagnostic info dialog + heap-snapshot analyzers. Triggers on "memory leak", "GPU memory", "tab bloat", "why is kolu slow", "debug performance", "zombie canvas", "WebGL leak", or any
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 GitHub Actions workflows locally with act on macOS. Use when validating workflow wiring or a job before pushing. Not for authoring the workflow itself (ci-workflow-authoring).
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。
Add or modify a GitHub Actions job. Use when editing a file under .github/workflows/. Not for running a workflow locally (local-ci-act) or release signing (release-signing).
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 high-quality, model-aware system prompts for any LLM (Claude, GPT, Gemini, open-source, etc.). Use this skill whenever the user wants to create, write, build, design, draft, or improve a system prompt, system instructions, or custom instructions for any AI model. Also trigger when the user asks about prompt engineering, prompt design, prompt optimization, or wants to define behavior for an AI assistant, chatbot, agent, or any LLM-powered application — even if they don't explicitly say "system prompt". Covers all use cases including chatbots, agentic systems, tool-use workflows, content generation, data extraction, code assistants, and multi-turn conversations.
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。
Professional PDF financial plan generator. Scans current working directory for FINANCE-*.md files, extracts scores and financial data, then runs the bundled Python ReportLab script to produce a polished, client-ready PDF with cover page, Financial Health Score gauge, score breakdown, cash flow, debt, retirement, portfolio, and prioritized action plan. Output: FINANCE-PLAN.pdf.
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。
Net worth tracker and milestone planner. Calculates current net worth, projects future net worth at retirement, tracks milestones ($100K, $250K, $500K, $1M, $5M, $10M), benchmarks against age-based wealth targets and percentile rankings, and applies the Millionaire Next Door formula. Identifies the user's current wealth accumulation phase and the next action that moves the needle. Produces FINANCE-NETWORTH.md.
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。
60-Second Financial Snapshot — fast assessment of financial health based on six core inputs (income, expenses, savings, debt, age, retirement goal). No subagents. Produces a compact terminal scorecard with savings rate, DTI ratio, emergency fund coverage, retirement on-track status, and top 3 priority actions in under 40 lines.
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。