2,399 件 ・ 関連度順
概要と使いどころ
Generates a plain English summary of everything that happened across all your accounts this week. What improved, what declined, what needs immediate attention, and what to prioritize next week. The Monday morning briefing that saves you an hour of pulling reports and context-switching between platforms. 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。
Takes your raw campaign performance data and writes the executive summary paragraph that goes at the top of the report. The plain English explanation of what happened, why it happened, and what's being done about it. The part every client actually reads. 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。
Catches unusual performance changes across your accounts — CPC spikes, CVR drops, spend surges, impression collapses, CTR shifts — and flags them with context about what likely changed. The goal is to catch problems in hours instead of discovering them days later during a routine check. 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。
Analyzes how your campaigns perform across mobile, desktop, and tablet. Identifies where device performance diverges significantly and recommends bid adjustments, campaign splits, or creative/landing page changes to capture the gap. 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。
Reviews your landing pages against the ads driving traffic to them. Checks for message match between ad copy and page content, CTA clarity, above-the-fold alignment, form friction, and flags any disconnects between what the ad promises and what the page delivers. 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。
Breaks down Quality Score components for your Google Ads keywords — expected CTR, ad relevance, and landing page experience — and tells you exactly which component is dragging each keyword down, with specific fixes ranked by potential CPC impact. Platform: Google.
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。
Pulls competitor ads from Meta Ad Library and Google Ads Transparency Center, categorizes their messaging angles, formats, CTAs, and creative types, then identifies gaps in their approach you can exploit and patterns worth testing in your own campaigns. Platform: 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。
Rewrite existing pages so AI assistants can extract, quote, and cite them. Claude restructures your content into answer-ready blocks — direct answers, comparison tables, stats with sources, schema — without wrecking the human reading experience. Platform: 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。
Analyzes frequency data across your Meta campaigns, identifies where you're overserving ads to the same people, and recommends frequency caps by campaign objective. Tells you the point where additional impressions stop driving conversions and start burning money. Platform: 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。
Analyzes your campaign history, conversion volume, CPA targets, and auction dynamics, then recommends the right bid strategy for each campaign — manual CPC, target CPA, target ROAS, maximize conversions, or maximize conversion value. Not a blanket recommendation, but campaign-by-campaign based on the data. Platform: Google.
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。
Tracks daily spend against monthly budget targets across all campaigns and accounts. Tells you exactly where you'll land at current pace, flags campaigns that are over or underspending, and calculates the daily budget adjustments needed to hit your target by month end. 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。
Maps out how users move through your funnel from first ad click to conversion. Identifies where the biggest drop-offs happen, which campaigns contribute most at each stage, and how long the typical conversion path takes across different audience segments. 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。
Find the exact pages AI assistants cite when answering questions in your category, and identify which ones you can get into. Claude clusters the cited sources, scores each by attainability, and outputs an outreach/content plan. Platform: 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。
Runs your conversion data through different attribution models side by side — last click, first click, linear, time decay, position based, and data-driven. Shows you how credit shifts between campaigns depending on the model so you can make better budget decisions instead of over-investing in last-touch campaigns. 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。
Craft better prompts using proven optimization techniques — use when your prompt needs refinement
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。
Interrogate a plan, decision, or design one question at a time until it holds — use to stress-test your own thinking before committing to it
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。
Archive the current thread and release its runtime. Use when the user explicitly asks to "self-archive", "archive yourself", or "archive this thread".
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 of a PR, branch, or your own uncommitted work across eight dimensions — security, correctness, test coverage, API/compatibility, usability, documentation, code quality, performance. Sizes the diff, reviews inline or fans out reviewers off a shared brief, verifies findings against code, reports a grouped list with a shape verdict, fixes on approval. Use for "review this PR", "/pr-review 3011", or a pre-flight self-review before submitting; add "thorough" for adversarial verification.
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。
Privacy-respecting metasearch using your local SearXNG instance. Search the web, images, news, and more without external API dependencies.
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。
Show results as interactive UI inside Codeg's chat (cards, tables, charts, tabs, accordions, badges, progress bars, simple forms) by writing a json-render spec code block in your reply. Use when the user invokes this skill or asks to see something as a card, table, chart, dashboard or other visual layout in Codeg.
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 publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.
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, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche. Identifies high-value opportunities based on search volume, competition, intent, and business relevance. Generates topic clusters. For building a dated editorial calendar from your own Search Console data, use `content-planner` instead — this skill is seed-driven keyword discovery, not calendar scheduling. Use when asked to "find keywords", "keyword research", "keyword analysis", "search volume", "keyword difficulty", "content ideas from a seed", or any keyword discovery 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。
Cross-model second opinion from Google Gemini — a different AI reviewing the same changes, with deep Google ecosystem knowledge. Three modes: review (pass/fail gate for Google Ads campaigns, SEO metadata, or code), challenge (adversarial stress-test that tries to break your changes), and consult (open Q&A with Gemini on Google Ads strategy, SEO best practices, or implementation questions). Use when the user says "gemini review", "ask gemini", "gemini challenge", "second opinion from gemini", "consult gemini", "stress test with gemini", "what would gemini say", "cross-model review", or "get another opinion". Voice aliases: "gem", "gemini check". Especially useful for Google Ads changes, SEO metadata updates, campaign structure decisions, keyword strategies, and bid/budget changes — Gemini has native Google ecosystem knowledge that complements Claude's analysis.
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。