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概要と使いどころ
Transform one long-form piece into multiple platform-specific content derivatives including LinkedIn posts, tweet threads, email snippets, ad hooks, and video scripts while maintaining voice consistency. Use when given a blog post, article, or pillar content to atomize across channels. 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。
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。
Designs statistically valid split tests for ads, audiences, landing pages, or bid strategies. Calculates required sample sizes before you start, monitors results during the test, and calls winners when statistical significance is actually reached — not when you feel like one is winning. 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。
Scans your Google and Meta accounts for money being spent on search terms, placements, audiences, and ads that produce zero or near-zero conversions. Delivers clean exclusion lists you can upload directly. 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。
Identifies where your own keywords and campaigns are competing against each other in Google Ads auctions. Finds duplicate keywords across campaigns, overlapping match types that trigger the same queries, and ad groups stealing traffic from each other — all of which inflate your CPCs and mess up your 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。
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.
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。
Monitors your ads for early signs of fatigue before performance fully collapses. Tracks frequency buildup, CTR decay, CPM increases, and engagement drops across all active creatives and tells you which ones need rotation now vs next week. 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。
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。
Import contacts (address book entries) into TRES Finance from a CSV or XLSX file. Use this skill whenever the user wants to import, upload, or bulk-add contacts, address labels, or address book entries into TRES — whether from a file they filled in after using the export-3rd-party-contacts skill, or from any CSV/XLSX that maps addresses to names. Trigger phrases include: 'import contacts', 'upload contacts', 'add contacts from file', 'import address book', 'load contacts into TRES', 'bulk label addresses', 'import the contacts file', 'upload the filled contacts sheet'. Also trigger when the user says something like 'I filled in the contacts file, now import it' or 'here is my contacts spreadsheet, please upload it to TRES'. Do NOT trigger for exporting or extracting unidentified addresses — that's the export-3rd-party-contacts skill. Do NOT trigger for viewing or searching the existing address book.
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 log files to troubleshoot errors, identify peak error periods, and produce error clustering, frequency statistics, and time distribution reports. Supports JSON, syslog, and Nginx formats with automatic detection. Use when a user uploads a .log file and asks to analyze errors, find patterns, debug issues, or get distribution stats.
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。
Upload files to Cloudflare R2, AWS S3, or any S3-compatible storage (like MinIO) and generate secure, time-limited presigned download links with configurable expiration, typically set to 5 minutes. Use when the user needs to upload a file to cloud storage and get a shareable link, or mentions R2, S3, presigned URLs, temporary links, or file uploads with expiration.
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 skill should be used when the user asks to "use Metasploit for penetration testing", "exploit vulnerabilities with msfconsole", "create payloads with msfvenom", "perform post-exploitation", "use auxiliary modules for scanning", or "develop custom exploits". It provides comprehensive guidance for leveraging the Metasploit Framework in security assessments.
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 skill should be used when the user asks to "apply skill improvements", "update skill from plan", "execute improvement plan", "fix skill issues", "implement skill recommendations", or mentions applying improvements from quality review reports. Reads improvement-plan-{name}.md files generated by skill-quality-reviewer and intelligently merges and executes the suggested changes to improve Claude Skills quality.
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。
Strip AI writing patterns from text. Checks 24 patterns across 4 categories (structural, lexical, rhetorical, formatting) with academic economics adaptation. This skill should be used on any text that reads too "AI-generated", or as a final pass on drafted sections. Triggers on "humanize", "de-AI", "make it sound natural", or "strip AI 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。
Diverga HUD (Heads-Up Display) management skill. Configure and manage the research project statusline display. Supports multiple presets: research, checkpoint, memory, minimal. Triggers: "hud", "statusline", "display settings"
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。
Prose quality checker for Quarto (.qmd) files, grounded in William Zinsser's *On Writing Well* (30th Anniversary Edition). Checks for clutter, weak verbs, hollow qualifiers, clichés, inflated academic voice, poor leads and endings, pronoun and tense inconsistency, and unclear explanation. Produces a structured markdown report organized by document section — never modifies the source file. Use when asked to improve prose quality, tighten writing, reduce clutter, or apply Zinsser's writing principles to a draft. For grammar and punctuation, use the proofread skill. For APSA style rules, use the apsa-style skill. Supports an optional output-file argument and an optional @sec-label argument to restrict checking to one section.
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。
Download, split, and deeply read academic PDFs. Use when asked to read, review, or summarize an academic paper. Splits PDFs into 4-page chunks, reads them in small batches, and produces structured reading notes — avoiding context window crashes and shallow comprehension.
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 a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
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。
Revise an academic paper based on journal referee reports. Reads referee comments from review report or annotated manuscript, then directly modifies main.tex one comment at a time with user approval. Generates response letter after revision. Trigger when user says "referee revise" / "paper-referee-revise" / "审稿意见修改" / "根据审稿人意见修改" / "referee report".
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 a complete academic literature survey from scratch using multi-agent orchestration. Searches academic databases (OpenAlex, CrossRef, Unpaywall), downloads PDFs, builds BibTeX, drafts a LaTeX review, compiles it, reviews for quality, and revises based on feedback — all automated. Use this skill whenever the user asks to "generate a literature review", "write a survey paper", "review recent papers on [topic]", "create a survey of [field]", "综述", "文献综述", "survey papers in top journals", or wants a multi-agent pipeline to produce a publishable-quality literature review. Also trigger when the user wants to search multiple journals for papers on a topic and synthesize findings into a structured document. Works for any academic field but optimized for economics journals.
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。
Revise an academic paper based on internal review comments. Reads review report or annotated manuscript, then applies revisions one by one with user approval. Trigger when user says "self revise" / "paper-selfrevise" / "内部修改" / "根据审稿意见修改".
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。
Cost-benefit analysis. Produces economic NPV and financial NPV side by side, with BCR, optimism bias (with mitigation), Marginal Excess Tax Burden, real-terms rebasing, WELLBY / QALY / VPF wellbeing valuation, sensitivity, switching values, EANC for unequal-life options, validation gate, and a one-line headline verdict (socially worthwhile vs financially self-sustaining). Backed by the greenbook R package (HM Treasury Green Book primitives) when available, with graceful fallback. Supports HMT Green Book, EU Better Regulation, World Bank, ADB, and Victorian HVHR. Reads a longlist markdown file directly via --from.
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。
STATA code pattern library for empirical archival accounting research. Provides tested syntax from 126 peer-reviewed JAR (Journal of Accounting Research) replication files (2017-2025). Use when the user asks procedural questions like "How do I implement [method]?" or "Show me code for [technique]" — including: entropy balancing, propensity score matching (PSM), difference-in-differences (DiD), regression discontinuity (RDD), instrumental variables (IV), event studies (CAR/BHAR), survival analysis, Fama-MacBeth regressions, bootstrap, quantile regression, reghdfe/xtreg/areg, clustering standard errors, fixed effects, esttab/outreg2 table formatting, winsorization, leads/lags. Users can specify their variables (e.g., treatment, outcomes, controls) and receive adapted syntax. NOTE: This skill provides code patterns from published papers, not research design advice.
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。