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概要と使いどころ
When the user wants to optimize images for search engines and performance. Also use when the user mentions "image SEO," "alt text," "image captions," "figcaption," "image optimization," "WebP," "lazy loading," "LCP," "image sitemap," "responsive images," "srcset," "image format," or "hero image optimization." For CWV, use core-web-vitals.
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。
Designing quizzes, personality assessments, and recommendation tools that segment users into actionable categories rather than generating clicks for clicks' sake. Question architecture, scoring algorithms, result categorization, recommendation mapping, lead capture integration. Honest about clickbait-quiz (engagement only), vanity-result (entertaining, not useful), and actionable-segmentation (genuine categorization that drives next-step recommendations) patterns. Triggers on quiz, assessment, personality test, recommendation tool, scorecard, diagnostic, fit evaluator, what-type-of-X-are-you, persona quiz. Also triggers when an audience needs a categorization-driven lead magnet, when a vanity quiz is producing engagement but no qualified leads, or when an assessment is being scoped for the first time.
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 a comprehensive on-page SEO audit or optimization pass covering title tags, meta descriptions, header structure, content quality, internal links, image optimization, URL hygiene, and on-page schema. Use this skill whenever the user asks to optimize a page, audit on-page SEO, fix titles or meta tags, review header structure, check internal linking, improve a single URL's search performance, or write SEO-friendly copy. Triggers on on-page SEO, page audit, title tag, meta description, H1, header structure, internal links, image alt, URL slug, page optimization, optimize this page, SEO this page. Also triggers for any single-page review where ranking, click-through, or relevance signal quality is the goal, even if the user does not say 'SEO' explicitly.
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 existing content across a site to decide what to keep, update, merge, redirect, or delete. Use this skill whenever the user wants to audit existing content, fix content decay, resolve keyword cannibalization, prune underperforming pages, prioritize content updates, or apply a keep/update/merge/redirect/delete framework to a content library. Triggers on content audit, content decay, content refresh, cannibalization, keyword cannibalization, prune content, delete pages, redirect old pages, content inventory, what to keep, what to update, content scorecard, evergreen refresh. Also triggers when traffic is dropping site-wide and the cause might be content quality, even if 'audit' is not said explicitly.
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 and fix web performance issues including Core Web Vitals (LCP, INP, CLS), bundle size, asset optimization, render performance, and runtime efficiency. Use this skill whenever the user wants to improve page speed, fix Core Web Vitals, optimize assets, reduce bundle size, debug slow renders, or systematically improve a site's performance. Triggers on performance, page speed, Core Web Vitals, LCP, INP, CLS, FID, TTFB, bundle size, code splitting, image optimization, lazy loading, render blocking, slow page, performance audit, Lighthouse score. Also triggers when traffic or conversion is dropping due to perceived slowness.
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。
Product manager toolkit covering RICE prioritization, customer interview analysis, PRDs, and discovery frameworks. Use for feature prioritization, user research synthesis, requirement documentation, or product strategy.
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。
Popup and modal optimization for conversion. Covers exit-intent, slide-ins, banners, timing optimization, frequency capping, audience targeting, compliance, and A/B testing frameworks for lead capture, promotions, and announcements.
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。
In-app paywall and upgrade screen optimization covering feature gate design, usage limit UX, trial expiration flows, upgrade trigger timing, save offer strategy, and ethical monetization 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。
Form optimization for lead capture, contact, demo request, application, and checkout forms. Covers field-cost analysis, multi-step form design, validation UX, mobile optimization, and A/B testing frameworks.
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。
When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions 'AI SEO,' 'AEO,' 'GEO,' 'LLMO,' 'answer engine optimization,' 'generative engine optimization,' 'LLM optimization,' 'AI Overviews,' 'optimize for ChatGPT,' 'optimize for Perplexity,' 'AI citations,' 'AI visibility,' 'zero-click search,' 'how do I show up in AI answers,' 'LLM mentions,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.
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。
Expert blueprint for Battle Royale games including shrinking zone/storm mechanics (phase-based, damage scaling), large-scale networking (relevancy, tick rate optimization), deployment systems (plane, freefall, parachute), loot spawning (weighted tables, rarity), and performance optimization (LOD, occlusion culling, object pooling). Use for multiplayer survival games or last-one-standing formats. Trigger keywords: battle_royale, zone_shrink, storm_damage, deployment_system, loot_spawn, networking_optimization, relevancy_system, snapshot_interpolation.
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。
Expert patterns for multi-platform exports including export templates (Windows/Linux/macOS/Android/iOS/Web), command-line exports (headless mode), platform-specific settings (codesign, notarization, Android SDK), feature flags (OS.has_feature), CI/CD pipelines (GitHub Actions), and build optimization (size reduction, debug stripping). Use for release preparation or automated deployment. Trigger keywords: export_preset, export_template, headless_export, platform_specific, feature_flag, CI_CD, build_optimization, codesign, Android_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。
MCP server optimization and transport layer enhancement for claude-flow v3. Implements connection pooling, load balancing, tool registry optimization, and performance monitoring for sub-100ms response times.
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 implementing localization (i18n/l10n) — TranslationServer, CSV/PO translation files, locale switching, RTL support, and pluralization in Godot 4.3+
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。
Optimize content for AI Overviews (formerly SGE), ChatGPT web search, Perplexity, and other AI-powered search experiences. Generative Engine Optimization (GEO) analysis including brand mention signals, AI crawler accessibility, llms.txt compliance, passage-level citability scoring, and platform-specific optimization. Use when user says "AI Overviews", "SGE", "GEO", "AI search", "LLM optimization", "Perplexity", "AI citations", "ChatGPT search", or "AI visibility".
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。
Image optimization analysis for SEO and performance. Checks alt text, file sizes, formats, responsive images, lazy loading, CLS prevention, image SERP rankings (via DataForSEO), and image file optimization (WebP/AVIF conversion, IPTC/XMP metadata injection). Use when user says "image optimization", "alt text", "image SEO", "image size", "image audit", "optimize images", "image metadata", "image SERP", "convert to webp", or "image file optimize".
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 A/B test plans and optimization checklists for your App Store product page — icon, screenshots, and app previews. Use when running Product Page Optimization tests or improving conversion rates.
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。
Monetization strategy for iOS/macOS apps. Covers readiness assessment, pricing model selection, tier structuring, free trial strategy, and implementation guidance. Use when deciding what to charge, how to price, or planning monetization end-to-end.
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 analysis and visualization of alternative splicing (AS) events from RNA sequencing data remains challenging. SpliceWiz is a user-friendly and performance-optimized R package for AS analysis, by processing alignment BAM files to quantify read counts across splice junctions, IRFinder-based intron retention quantitation, and supports novel splicing event identification. We introduce a novel visualization for AS using normalized coverage, thereby allowing visualization of differential AS across
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。
This R package supports interactive visualization of multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques using shiny. The cytoviewer interface is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with SingleCellExperiment and SpatialExperiment objects for metadata visualization and supports image do
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。
Expert knowledge for Azure Carbon Optimization development including troubleshooting, security, and integrations & coding patterns. Use when using Carbon Service REST API, Python exports, RBAC roles, emissions data quality, or dashboard issues, and other Azure Carbon Optimization related development tasks. Not for Azure Cost Management (use azure-cost-management), Azure Impact Reporting (use azure-impact-reporting), Azure Monitor (use azure-monitor), Azure Policy (use azure-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。
Reusable approval-loop pattern for fanning out lead personalization across parallel Claude Code Task sub-agents. Shows the user 1 sample personalization, collects feedback, runs 10 more, approves, runs 10 more — stops when 2 consecutive rounds have zero edits, then scales to the full list. ALWAYS uses Claude Code Task tool sub-agents — never an external Anthropic/OpenAI API key. Use when any skill needs per-lead custom variables (situation lines, value lines, CTAs).
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。
Amazon search ranking optimization and A9 algorithm mastery. Comprehensive SEO strategy, indexing optimization, keyword ranking improvement, and search visibility enhancement. Use when the user asks about Amazon SEO, A9 algorithm, search ranking, or product discoverability.
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 Amazon profit analysis and revenue optimization. Revenue waterfall analysis, hidden fee identification, ACoS impact assessment, return cost calculation, and profitability optimization strategies. Use when the user asks about Amazon profit analysis, profitability calculation, fee analysis, margin optimization, or revenue breakdown.
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。