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Transform reference photographs and visually dense images into sparse, recognizable, high-saturation flat-vector-style illustrations through semantic compression rather than literal tracing. Use when the user asks for photo-to-flat illustration, photo-to-vector-style redraw, 照片转扁平插画, 无渐变高饱和插画, iconification, visual simplification, composition-preserving abstraction, a consistent minimal illustration set, or revisions that remove gradients, glow, texture, blur, clutter, text, logos, numbers, or UI. Default to human-perceived semantic complexity 6 out of 10 or lower, fixed-HSB solid fills, crisp boundaries, and no gradients or light-halo effects.

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。

Access ENCODE uniform analysis pipelines, generate user-specific Nextflow/WDL pipelines, manage compute resources, and integrate with cloud platforms. Use when the user wants to understand ENCODE pipelines, run pipelines on their own data, generate custom Nextflow workflows from ENCODE pipeline code, check compute requirements (CPU/GPU/memory), run pipelines in background, or integrate with Google Cloud, AWS, or other cloud platforms. Also use when the user asks about ENCODE pipeline outputs, processing standards, software versions, or wants to replicate ENCODE processing. Covers local execution, HPC, and cloud deployment with resource-aware scheduling. Use this skill for ANY pipeline execution, workflow generation, or compute resource management task involving ENCODE data.

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。

Cross-reference ENCODE data with PubMed, bioRxiv, ClinicalTrials.gov, Open Targets, GTEx, ClinVar, GWAS Catalog, gnomAD, Ensembl, and other scientific databases. Use when the user wants to find publications, preprints, or clinical trials related to ENCODE experiments, chain ENCODE data with other scientific MCP servers, or build translational pipelines from genomic data to clinical application.

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 rigorous cross-study meta-analysis of scRNA-seq data from ENCODE, integrating multiple single-cell transcriptomic datasets for a tissue/cell type. Use when the user wants to answer "what cell types exist in my tissue and what genes define them?" by combining scRNA-seq data across donors, labs, and platforms. Follows the Mawla et al. 2019 framework for assessing cross-study reproducibility, TIN-based quality filtering, and detection-limit-aware interpretation. Handles batch correction (Harmony/Seurat), dropout awareness, cross-contamination artifacts, and platform-specific biases. Use this skill for ANY scRNA-seq integration task, cross-dataset comparison, cell atlas construction, or reproducibility assessment involving ENCODE single-cell data.

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 ENCODE functional genomics data for disease mechanism research. Use when the user wants to connect GWAS variants to regulatory elements, annotate disease-associated loci with functional data, identify therapeutic targets from epigenomic data, build disease regulatory models, cross-reference with clinical trials and drug databases, or conduct any disease-focused, pathology-driven, or clinical variant interpretation workflow. Covers the full pipeline from disease-tissue mapping through GWAS variant annotation, heritability enrichment, cancer epigenomics, drug target identification, and clinical trial cross-referencing. Integrates ENCODE with Open Targets, PubMed, ClinicalTrials.gov, and bioRxiv.

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。

Spring Boot 4 REST API implementation patterns. Use when creating REST controllers, REST endpoints, request validation, exception handlers with ProblemDetail (RFC 9457), API versioning, content negotiation, WebFlux reactive endpoints, HTTP clients with @HttpExchange, JSON serialization with Jackson 3, error handling, or CORS configuration. Covers @RestController patterns, Bean Validation 3.1, global error handling, and declarative HTTP clients.

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 brand icons as SVG and produce all platform assets including favicon package (ICO, SVG with dark mode, apple-touch-icon), PWA manifest icons, and mobile app icons. Use when user runs /icon-forge, requests "brand icon", "favicon generation", "app icon", or "svg logo" for a project.

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。

Validate skills against Anthropic best practices for frontmatter, structure, content, file organization, hooks, MCP, and security (62 rules in 8 categories). Use when creating new skills, updating existing skills, before publishing skills, reviewing skill quality, or when user mentions "validate skill", "check skill", "skill best practices", "skill review", or "lint skill".

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。

Explains complex code through clear narratives, visual diagrams, and step-by-step breakdowns. Use when user asks to explain code, understand algorithms, analyze design patterns, wants code walkthroughs, or mentions "explain this code", "how does this work", "code breakdown", or "understand this function".

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。

Technical SEO audit across 8 categories: crawlability, indexability, security, URL structure, mobile, Core Web Vitals, structured data, and JavaScript rendering. Enhanced with live GSC (indexing status, crawl data) and Ahrefs (backlink profile) data when MCPs are available. Use when user says "technical SEO", "crawl issues", "robots.txt", "Core Web Vitals", "site speed", or "security headers".

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。

Pre-publish (or retroactive) content-quality gate implementing Google's official self-assessment questions from the creating-helpful-content doc, plus 2024 spam-policy red flags. Verdict: PUBLISH / REVISE / RETHINK. Use when user says "helpful content", "people-first", "content self-assessment", "is my content helpful", or "content quality gate".

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。

Discover newly ranking keywords using Google Search Console data. Finds queries that had zero clicks or impressions in the prior 28 days but started appearing in the current period, revealing emerging content opportunities. Use when user says "new keywords", "new rankings", "keywords started ranking", "recently ranking", or "new 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。

Audit robots.txt for AI crawler access policies. Checks GPTBot, ClaudeBot, PerplexityBot, Google-Extended, and other AI crawlers. Use when user says "robots AI", "AI crawlers", "block AI", "allow AI bots", "AI crawl 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。

Standalone E-E-A-T scoring rubric for a URL or content draft. Scores Experience, Expertise, Authoritativeness, and Trust 0-5 each using concrete detectable signals, framed per Google's creating-helpful-content doc. Use when user says "E-E-A-T", "EEAT", "experience expertise", "trust signals", or "author authority".

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。

Dedicated Core Web Vitals deep-dive: pull field data (CrUX / PageSpeed Insights), fall back to Lighthouse lab data, score LCP, INP, and CLS against Google's thresholds at the 75th percentile, and run per-metric diagnosis playbooks with concrete fixes. Use when user says "core web vitals", "CWV", "LCP", "INP", "CLS", "page speed metrics", or "field data".

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 Lighthouse audit against any URL via the local Lighthouse CLI or the PageSpeed Insights API fallback, parse category scores and failed audits, and map every failed audit ID to its official Chrome docs page plus a one-line fix. Use when user says "lighthouse", "lighthouse audit", "run lighthouse", "lighthouse score", or "pagespeed".

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。

Detect ranking drops and lost traffic using Google Search Console data. Compares the last 28 days against the prior 28-day period to surface pages and keywords with the biggest declines. Use when user says "GSC drops", "ranking drops", "lost traffic", "pages losing rankings", or "keyword drops".

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 branded vs non-branded traffic split using Google Search Console data. Shows what percentage of organic clicks come from brand name searches vs generic queries. Requires user to confirm brand terms before analysis. Use when user says "brand vs nonbrand", "branded traffic", "brand queries", "non-brand traffic", or "branded vs generic".

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。

Identify indexing problems and coverage issues using Google Search Console URL inspection data. Checks up to 20 pages for indexing status, coverage state, robots.txt state, and last crawl date. Use when user says "index issues", "indexing problems", "not indexed", "indexing coverage", or "why is my page not indexed".

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。

Compare Google Search Console performance between two time periods to identify trends and changes. Supports month-over-month (MoM), year-over-year (YoY), or custom date ranges. Use when user says "GSC compare", "period comparison", "month over month", "year over year", "compare performance", "MoM", or "YoY".

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。

Holistic page-experience self-assessment mirroring Google's own question list: Core Web Vitals, HTTPS, intrusive interstitials, mobile usability, content prominence, and ad distinguishability. Use when user says "page experience", "UX signals", "interstitials", "mobile friendly", or "HTTPS check".

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。

Detect keyword cannibalization by identifying queries where multiple pages are competing for the same ranking. Uses Google Search Console data to find queries appearing across 2 or more pages. Use when user says "keyword cannibalization", "same keyword multiple pages", "cannibalizing keywords", or "duplicate rankings".

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 quick SEO wins by identifying high-impression, low-CTR keywords using Google Search Console data. Surfaces keywords already ranking where better titles or content expansion could quickly boost traffic. Use when user says "GSC opportunities", "quick wins", "low CTR keywords", "high impressions low clicks", or "easy SEO wins".

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。

Detect content decay by identifying pages that are losing both clicks and impressions over a 90-day comparison window in Google Search Console. Surfaces pages with true long-term decline (not seasonal variation) and assigns decay severity ratings. Use when user says "content decay", "declining pages", "losing rankings", "pages losing traffic over time", or "90 day decline".

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。