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概要と使いどころ
Compares your Meta ad sets and identifies where audiences overlap significantly, causing your ads to compete against each other in the same auctions. Tells you exactly which ad sets are cannibalizing each other and how much it's costing you in inflated CPMs. Platform: Meta.
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Analyzes performance by day of week and hour of day across your campaigns. Identifies when your ads perform best and worst, recommends ad schedule adjustments with estimated savings, and tells you exactly what you'd give up by restricting hours. Platform: Google and Meta.
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。
Evaluates your campaign and ad set structure against your actual goals and budget. Flags over-segmentation that fragments your data, under-segmentation that hides performance differences, budget allocation issues, and consolidation opportunities that would improve algorithmic delivery and your ability to optimize. Platform: Google and Meta.
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。
Competitor page gap analysis — take a query you want to win and the pages currently outranking you, and produce a concrete brief on what to add or change to compete. Compares content depth and coverage (subtopics they cover that you don't), structure (headings, format, tables, media), search-intent match, E-E-A-T signals, schema/rich-result eligibility, internal linking, and on-page optimization — across your page vs. the top-ranking competitors. Use this skill whenever the user wants to know why a competitor outranks them on a specific query, what a top-ranking page does better, a content-gap analysis against specific competitor URLs, or a brief to beat a specific SERP. Trigger on: "why does competitor X outrank me", "content gap analysis", "competitor page analysis", "what does the top result have that I don't", "how do I beat this page", "analyze competitor pages", "SERP gap", "compete for [keyword]". For seed keyword discovery use /keyword-research; for a content calendar use /content-planner.
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。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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。
Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)
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。
Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)
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。
Extract subtitles/transcripts from YouTube videos. Triggers: "youtube transcript", "extract subtitles", "video captions", "视频字幕", "字幕提取", "YouTube转文字", "提取字幕".
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。
Implement Google's Material Design 3 (Material You) UI system. Primary: Jetpack Compose Material3 (MaterialTheme, components, adaptive layout). Also Flutter and limited web (@material/web, maintenance mode). Covers tokens, 30+ components, layout, theming, M3 Expressive (platform matrix), and accessibility. Use when: "material design", "MD3", "material you", "Jetpack Compose", "MaterialTheme", "material component", "md3 button".
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。
Make a genuinely good drink from the bottles already on your shelf — no special trip, no 12-ingredient recipe. Use when asked what can I make with [spirits], cocktail from what I have, I've got [bottles] what can I drink, or make me a drink without buying anything. Produces two or three cocktails you can build right now with ratios, a method, sensible substitutions for what you're missing, and a zero-proof version — scaled to how many you're making.
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。
Get started birding from where you are — what you're likely to see, how to tell confusing species apart, and a simple life-list to track sightings. Use when asked to start birdwatching, what bird did I see, help me identify a bird, or set up a birding log. Produces a likely-species list for your area and season, ID prompts (the field marks and sounds that separate look-alikes), a beginner gear-and-timing note, and a lightweight life-list format — pointing you to a live ID app to confirm any specific sighting.
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。
Set up a backup system that actually protects your photos, files, and devices — built on the 3-2-1 rule and, crucially, tested so it works when you need it. Use when asked how to back up my data, set up backups, protect my photos/files, or what's a good backup strategy. Produces a 3-2-1 plan tailored to your devices and data, specific what-to-back-up priorities, an automation setup so it happens without you, a restore-test step, and protection against the failure that ruins backups (ransomware/sync-deletes reaching the backup).
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。
Figure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or something else. Produces a match between your task and the right kind of AI tool (with why), the trade-offs that matter for your case, when the answer is a non-AI tool or plain human effort, and how to try it cheaply before committing — so you pick by fit, not by hype or habit.
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。
Work with YouTube: read channels, videos, search, playlist items; upload videos and post comments (with confirmation). Trigger phrases: youtube, videos, upload video, youtube comment.
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。
Daily meeting preparation system that checks your calendar each morning, deeply researches external attendees (LinkedIn, company info, GitHub, past notes), and sends you personalized briefs via email (1 per person). Use when you want automated preparation for upcoming meetings with context about each person you're meeting.
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 the user mentions SwiftUI layout review, adaptive layout issues, GeometryReader problems, or multi-device layout checking.
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 the user wants to find YouTube content on any topic: searching for videos or channels, finding creators who cover a subject, discovering tutorials, talks, or expert discussions, or looking up a channel by name or handle. Also use proactively when the user wants to research a topic and YouTube is a good source. Not for account management or written-source-only research.
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 YouTube is relevant: pasted video links or IDs, @handles, quick video lookups, summaries, channel latest uploads, topic search, or any request involving YouTube content — even if YouTube is not mentioned explicitly. Covers transcripts, search, and channel latest. Not for uploads or account 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。
Compose pages and sites that read as their vertical: ecommerce-catalog storefronts that look like storefronts, hospitality-food sites that look like restaurants, b2b-manufacturer sites that look industrial. Use this skill whenever the user wants to build a site that looks like the vertical it serves, fix a build that reads as generic or off-vertical, build to an experience bar produced by competitor-experience-audit, or compose pages with the merchandising, density, and layout conventions a credible site in the category is expected to carry. Triggers on vertical conventions, storefront layout, ecommerce layout, retail conventions, merchandising layout, category page composition, site composition, build to the experience bar, make it look like the vertical, off-vertical, looks generic, build conventions for a vertical, site grammar. Also triggers when a build that is technically clean reads wrong for its category, and the cause is composition, not visual taste.
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。
Step-by-step guide for creating your own Claude Skills, from deciding whether a skill is the right tool to writing the SKILL.md file, structuring reference material, and making it trigger reliably. Use when you want to package a workflow, framework, or repeated task into a reusable Skill, when an existing skill is not triggering or not loading the right context, when you are auditing a skill that is underperforming, or when you want to publish a skill for others. Also triggers when someone asks "how do I make a skill" or "what makes a good skill". Useful for individuals, teams, and anyone publishing skills publicly.
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。
Draft or review a DPDPA-compliant consent notice under India's Digital Personal Data Protection Act, 2023 and DPDPA Rules, 2025. Provide basic details about your business and this skill handles the rest - building a notice tailored to your operations, with all required sections, granular consent boxes, and internal notes for your team. If you have an existing notice or privacy policy that needs to comply with DPDPA, this skill revises it too, flagging key gaps and changes made.
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 your bar comes asking "show me how you billed AI-assisted work" — and ABA 512, Florida 24-1, California, New York, and DC all have opinions out — you need an artifact that survives review. billable-time produces it. From your Claude Code session logs, it drafts reviewable time entries plus a printable HTML audit packet with: SHA-256 chain of evidence (source files + matter.yml + active disclosure pack + verifiable artifact self-hash), attorney identity and signature block, a bar-opinion disclosure pack with starter language for five jurisdictions, and content-aware deterministic narratives derived from filename and tool shape — never from prompt text by default. The tool refuses to bill on its own. --strict mode refuses to ship the artifact if any audit invariant fails (broad routes, missing attorney, missing/unverified disclosure). Comes as a Node CLI and a self-contained browser version (no backend; JSONL never leaves the page). 15 invariant tests verify the contract. AGPL-3.0.
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 you want to draft, update, convert, or export a slide deck for a React/Next.js slide system (${SLIDE_DECK_REPO:-$HOME/code/your-slide-deck-site}/src/app/slides/). Writes TypeScript Slide[] arrays using your primitives (Eyebrow, Heading, Accent, Body, BulletList, Divider, TwoCol, GradientText), 12 cycling brand gradients, optional sections for "where am I" context, and speaker notes. Inspired by zarazhangrui/frontend-slides — "show, don't tell" for narrative (presents 3 angles, you pick) plus density modes (speaker-led vs reading-first). Four modes — new (draft from brief), update (modify existing, with overflow guards), ppt (convert legacy PPTX → React deck), export (Playwright snapshot existing React deck to standalone HTML, PDF, or Vercel URL — keeps brand). Triggers on "/slide-deck," "/slides new," "/slides export," "/slides update," "/slides ppt," "draft a deck," "deck for [topic]," "talk on [topic]," "keynote on [topic]," "internal deck for [audience]," "convert this pptx," "export this deck."
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 you want to extract content from a video — YouTube, Loom, Vimeo, Riverside, Zoom recording, local MP4, X/IG video, anything yt-dlp supports. Three depth modes user picks per invocation — transcript (just words, fast/free), visual (transcript + ffmpeg frame extraction + Claude vision pass on key moments), multimodal (Gemini native video ingestion if $GEMINI_API_KEY set, else dense Claude vision). Uses local Whisper for transcription (MLX-Whisper on Apple Silicon, faster-whisper elsewhere), falls back to platform-provided transcripts when available (Loom, Riverside, YouTube auto-subs). Saves to ~/Documents/videos/<source>-<slug>-<date>/ and optionally captures summary to second-brain raw/ as call-/meeting-/note-. Triggers on "/watch-video <url>," "watch this video," "transcribe this loom," "analyze this video," "summarize this recording," "key moments from this," "what happened in this video." This skill replaces and broadens the prior youtube-transcript 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。