2,106 件 ・ 関連度順
概要と使いどころ
Transform session learnings into permanent capabilities (skills, rules, agents). Use when asked to "improve setup", "learn from sessions", "compound learnings", or "what patterns should become skills".
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 title tags, meta descriptions, Open Graph, and Twitter cards for maximum click-through rate. Generates multiple A/B test variations with character counting and SERP preview. Use when asked to "optimize title tag", "write meta description", "improve CTR", "Open Graph tags", "fix my meta tags", "social media preview", "my click rate is low", "title optimization", or any meta tag task.
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。
Generative Engine Optimization (GEO) — make content rank in AI search answers from ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Audits existing content, rewrites for AI citation, and produces per-engine strategy. Use when asked to "optimize for AI search", "rank in ChatGPT", "GEO audit", "improve AI citations", "rank in Perplexity", "AI Overview optimization", "AI Overview ranking", "LLM SEO", "answer engine optimization", "AEO", "get cited by AI", "GEO", "generative engine optimization", "show up in ChatGPT", "appear in AI answers", "be cited by Perplexity", "SGE optimization", "Search Generative Experience", or "make my content show up in AI answers". Distinct from regular SEO — this targets generative engines, not traditional Google 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。
Full SEO audit combining Google Search Console, URL Inspection API, PageSpeed Insights, a technical crawl, keyword research, and metadata, schema, search intent and Core Web Vitals checks. Surfaces quick wins, diagnoses traffic drops and content gaps, and produces an actionable 30-day plan. Use whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, search visibility, technical SEO, URL indexing, or LCP, INP, CLS or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger.
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。
Single-page SEO audit: content quality under Google's E-E-A-T framework and Helpful Content guidelines, on-page factors, search intent, technical signals and readability. Pulls GSC data for the page, crawls the live HTML, checks metadata, schema, internal linking and depth, and produces a scored report with fixes. Use whenever the user wants to analyze a specific page or URL, not the whole site. Trigger on: "analyze this page", "audit this URL", "how is this page doing", "evaluate my blog post", "check this landing page", "page SEO", "content quality check", "is this page good enough", "review this page's SEO", "what's wrong with this page", "how can I improve this page", "page analysis", "single page audit", "content audit for [URL]", or any request naming a specific URL/page for SEO evaluation. If the user provides a specific URL (not just a domain), this is likely the right skill; use /seo-analysis for full-site audits 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。
Search Experience Optimization (SXO), the bridge between SEO and UX/CRO. Audits the journey from the SERP click to the on-page goal: click-through factors (title, meta, rich results), then post-click signals that keep users and drive conversions: above-the-fold relevance and intent match, page speed / Core Web Vitals, readability, clear CTAs, mobile usability, and what causes pogo-sticking back to Google. Use when the user has decent rankings but poor CTR or poor on-page conversion, wants better dwell time / engagement, less bounce, or a page experience aligned with search intent. Trigger on: "SXO", "search experience optimization", "good rankings but low CTR", "high bounce rate from search", "pogo-sticking", "improve dwell time", "SEO and conversion", "ranking but not converting", "engagement signals", "make this page convert search traffic". For pure landing-page conversion in ads use /google-ads-landing; for content quality use /seo-page.
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。
Score and diagnose Google Ads landing pages. Use when asked to audit a landing page, check landing page quality, diagnose high-CTR but low-conversion-rate ad groups, improve Quality Score's Landing Page Experience component, or compare an ad group's messaging against its landing page. Trigger on "landing page audit", "landing page score", "landing page quality", "why is my conversion rate low", "LPX", "landing page experience", "ad to page match", or when `/google-ads-audit` surfaces a high-CTR / low-CVR ad group.
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。
Measure JS SDK coverage or address measured coverage gaps. Use for coverage audits and metric regressions, not routine test additions.
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。
工作流组合：当一个任务明显需要多件思想武器接力时，提供四种标准组合模式（新项目启动、复杂问题攻坚、方案迭代优化、阶段复盘），定义调用顺序、每步交接物和终止条件。触发信号包括从零启动、疑难攻坚、迭代优化、阶段复盘；单一 skill 就够用时不触发。 English: Workflow patterns. When a task clearly needs several skills in sequence, pick one of four standard patterns (project kickoff, hard-problem assault, iterative improvement, stage retrospective) that fix the order, the handoff artifact between steps, and the stop condition. Skip when a single skill suffices.
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 and improves Browserbase Agent API demos through an Autobrowse-style outer loop: run a fixed task, collect Agent messages and session logs, score the result, revise one system-prompt heuristic, and confirm convergence. Use when creating a Browserbase Agents demo or POC, optimizing an Agent system prompt, diagnosing flaky Agent runs, or applying auto-research/autobrowse to the Browserbase Agents API.
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。
Perform language and framework specific security best-practice reviews and suggest improvements. Trigger only when the user explicitly requests security best practices guidance, a security review/report, or secure-by-default coding help. Trigger only for supported languages (python, javascript/typescript, go). Do not trigger for general code review, debugging, or non-security tasks.
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。
Umbrella skill for document workflows (PDF/DOCX/XLSX/PPTX). Dispatches to the most specific document skill to reduce noise and improve routing precision.
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。
Review and improve a dating profile on Tinder, Hinge or Bumble — rank the user's photos and pick the lead photo, check them against the app's official photo and AI-photo rules, then tighten the bio and suggest openers. Use when the user asks "which photo should be my first", "rate my dating photos", "can I use AI photos on Hinge/Bumble/Tinder", "fix my dating profile", or shares profile photos or a bio for feedback. Uses the free DatePhotos.AI MCP for official rules and photo scores when connected; falls back to a built-in checklist when it is not.
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。
Persistent task management and productivity intelligence via MCP. Captures tasks from conversation, plans your day, tracks patterns, and gives personalized recommendations that improve over 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。
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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 meeting transcripts and recordings to uncover behavioral patterns, communication insights, and actionable feedback. Identifies when you avoid conflict, use filler words, dominate conversations, or miss opportunities to listen. Perfect for professionals seeking to improve their communication and leadership skills.
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 your recent Claude Code chat history to identify coding patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth report to your Slack DMs.
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 Google Search Console exports or authorized API data to prioritize page improvements. Use for traffic changes, page/query opportunities, indexing evidence, and deciding when to leave recently edited or weakly supported pages alone.
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。
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
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。
Extracts and analyzes competitors' ads from ad libraries (Facebook, LinkedIn, etc.) to understand what messaging, problems, and creative approaches are working. Helps inspire and improve your own ad campaigns.
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。
Orchestration skill for NVIDIA Nemotron Speech (Riva) / NeMo ASR domain and language adaptation. Given a goal like "improve/fine-tune ASR for my domain or language", it scopes the task, picks the cheapest sufficient path (word boosting → n-gram LM → fine-tuning), delegates each stage to the right sub-skill (data generation, training, evaluation, deployment), and answers cost/time/data questions along the way.
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。
NOTE: your protein sequence and the retrieved MSA alignment are transmitted to external NVIDIA-hosted APIs (health.api.nvidia.com) on every call. Use local NIM containers for confidential or proprietary sequences. Run a complete protein structure prediction pipeline using NVIDIA BioNeMo NIMs: search for MSA alignments with MSA-Search (ColabFold), then predict the structure with OpenFold3 using the retrieved alignments. Use this skill whenever the user wants to predict a protein structure with maximum accuracy using MSA context, run the full AlphaFold3-style pipeline, generate MSA-informed structure predictions, or improve structure prediction accuracy by providing evolutionary information. Triggers on: MSA structure prediction pipeline, structure prediction pipeline, MSA-informed prediction, OpenFold3, ColabFold MSA, AlphaFold3 pipeline, protein structure, homology search, a3m alignment, UniRef30, NIM microservice. This pipeline chains MSA-Search and OpenFold3.
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 new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
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 openai-go during scheduled or repeated maintainer runs for correctness bugs, security weaknesses, performance problems, rough edges, non-idiomatic Go, test gaps, code organization, and architecture, then report one prioritized recommendation with evidence. Use for recurring proactive repository maintenance and rotating whole-codebase review; do not use for feature work, code changes, autonomous publishing, or pull-request stewardship.
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。