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概要と使いどころ
Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA standards. Use this skill to generate semantic ARIA for Web and accessibility traits for Web and Native platforms (iOS/Android).
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。
Upgrades existing websites and apps to premium quality. Audits current design, identifies generic AI patterns, and applies high-end design standards without breaking functionality. Works with any CSS framework or vanilla CSS.
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。
Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.
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。
Systematic QA testing for web applications, desktop apps, and workflows. Three tiers: QUICK (critical/high severity only — 5 min), STANDARD (+ medium severity — 15 min), EXHAUSTIVE (+ cosmetic — 30+ min). Tests user flows, finds bugs, reports with severity classification, and optionally auto-fixes with atomic commits. Produces before/after health scores and ship-readiness summary. Use when user says "test this", "QA", "find bugs", "does this work?", or "is it ready to ship?". Voice triggers: "quality check", "run QA", "test the app". For report-only (no fixes), use with --report-only flag.
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 this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
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。
Checks structured logging, health check endpoints, metrics collection, request tracing, log levels. Returns findings with severity, location, effort, recommendations.
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 5 root documentation files (PROJECT.md, docs/README.md, documentation_standards.md, principles.md, tools_config.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。
Checks hardcoded secrets, SQL injection, XSS, insecure dependencies, missing input validation. Returns findings with severity, location, effort, recommendations.
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。
Builds dependency graph, detects cycles (DFS), validates boundary rules, calculates coupling metrics (Ca/Ce/I, CCD/NCCD). Adaptive architecture detection.
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。
Checks compiler/linter errors, deprecation warnings, type errors, failed tests, build config issues. Returns findings with severity, location, effort, recommendations.
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。
Analyzes single pattern implementation, calculates 4 scores (compliance, completeness, quality, implementation), identifies gaps. Invoked by ln-640 or standalone.
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。
Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.
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。
Applies Anthropic's official brand colors and typography to any sort of artifact that may benefit from having Anthropic's look-and-feel. Use it when brand colors or style guidelines, visual formatting, or company design standards apply.
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。
Generates cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
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。
You are an AI Automation Agency strategist. Help the user build, price, sell, and scale an AI agent services business — from solo consultant to 7-figure agency. Every recommendation must be specifi...
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 AI safety and alignment audit framework for businesses deploying AI agents. Built around the UK AI Security Institute Alignment Project standards (2026), EU AI Act requirements, and N...
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。
Complete brand building and go-to-market system — from identity foundations through positioning, messaging, visual systems, and launch execution. Works for solopreneurs, startups, and established b...
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 complete board meeting packages — agenda, financial summary, KPI dashboard, risk register, and action item tracker.
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。
Answer Engine Optimization — get AI assistants to recommend your brand. Run AEO audits, build Answer Intent Maps, track AI recommendation positions, and maintain a 7-layer AEO infrastructure for any brand or product category.
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。
Advanced OpenClaw skill creation handler that executes the official 5-step research flow with comprehensive analysis and best practices. Ensures proper methodology when users request to create or modify OpenClaw/Moltbot/ClawDBot skills following official standards.
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。
Structured multi-criteria decision analysis for ranking options with weights, constraints, confidence, tradeoff reasoning, sensitivity analysis, and explainable recommendations. Use when the user asks for decision support, MCDA, weighted scoring, prioritization, vendor selection, route planning, hiring shortlist ranking, tool comparison, procurement decisions, or auditable agent decision 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。
Save any product to a universal wishlist. Converts any product URL into a one-click "save for later" link. Works with any retailer, any AI platform, zero setup.
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。
Adaptive testing engine with IRT/CAT, AI question generation, and personalized learning recommendations
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。
Transparent, rigorous research with full methodology — not a black-box API wrapper. Conducts exhaustive investigation through mandated 2-cycle research per theme, APA 7th citations, evidence hierarchy, and 3 user checkpoints. Self-contained using native OpenClaw tools (web_search, web_fetch, sessions_spawn). Use for literature reviews, competitive intelligence, or any research requiring academic rigor and reproducibility.
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。