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概要と使いどころ
React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.
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 a security scan on a deployed Power Pages site, fetches the latest scan report, and produces a plain-language summary. Scans the live site's public surface for vulnerabilities and surfaces issues by severity. Use when the user wants to scan, check, test, audit, or assess a published site, find vulnerabilities on production, view the latest scan report, see previous scan results, run a security audit, or asks "how safe is my live site?", "is my site vulnerable?", "audit my production site" — even if they say "find issues" or "check for problems" without mentioning "scan" or "security".
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。
Creates, edits, and manages Power Pages Server Logic files — server-side JavaScript that runs securely on the Power Pages runtime. Orchestrates the full lifecycle: gathering requirements, fetching documentation, implementing code, configuring site settings, and deploying. Use when the user wants to add server-side code, create API endpoints, or move logic from the browser to the server in their Power Pages site.
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。
Integrates Power Pages Web API into a site's frontend code with proper permissions and deployment. Orchestrates the full integration lifecycle: code integration, table permissions setup, and deployment for Dataverse CRUD operations. Use when the user wants to add Web API calls, connect to Dataverse, or add data fetching to their frontend.
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 the dpella/mcp Haskell library — types, handler shape, transports, and the conventions Emanote uses. Load this before adding MCP resources/tools/subscriptions so you don't re-discover the API by WebFetch.
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。
Fetch requested source material and prepare sourced engagement updates. Use to catch up from external notes or messages; applying updates requires a bound record and confirmation.
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。
Fetch today's trending topics from tophub.today across multiple platforms. Triggered when users ask "what's trending today", "hot topics", "今日热搜", or "微博热搜".
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。
Read and send email via IMAP/SMTP. Check for new/unread messages, fetch content, search mailboxes, mark as read/unread, and send emails with attachments. Works with any IMAP/SMTP server including Gmail, Outlook, 163.com, vip.163.com, 126.com, vip.126.com, 188.com, and vip.188.com.
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。
UI/UX best practices for web interfaces. Use when reviewing animations, CSS, audio, typography, UX patterns, prefetching, or icon implementations. Covers 11 categories from animation principles to typography. Outputs file:line findings.
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。
Connects to Oxylabs remote agent browsers over the Chrome DevTools Protocol (CDP) with Playwright or Puppeteer. Built-in anti-detection, residential proxies, geo-targeting, persistent sessions and profiles, session recording and live VNC inspection for debugging. Use instead of WebFetch or a local browser whenever a site renders with JavaScript, blocks bots (DataDome, Cloudflare, Akamai), needs a real browser session, screenshots or PDFs. Covers connection, retries, error recovery and safe scraping of protected targets without any human help.
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 an application or system — including one built quickly with AI coding agents — needs a security review with regulatory grounding: a STRIDE threat model, a LINDDUN privacy threat model, a dependency exposure screen against live CVE / CISA-KEV / EPSS data, or a selected, non-exhaustive screen of which EU security obligations (GDPR, NIS2, Cyber Resilience Act, AI Act) may apply and which need determination. Orchestrates the server-enforced threat-modeling workflows of the Ansvar Gateway MCP connector and grounds every regulatory statement in officially published text fetched at answer time — scope, role, and application-date limits stated, never a compliance verdict. Never simulates a workflow and never answers legal questions from model memory.
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。
Read, search, and download emails and attachments from Microsoft Outlook via OAuth2. Use when the user asks to (1) check, read, or fetch emails or messages from Outlook, (2) search emails by keyword, sender, or subject, (3) download email attachments such as contracts, NDAs, or documents, (4) chain email content into other skills (e.g. "read the latest email from X and review the attached NDA"), or (5) any task involving Microsoft Outlook, Office 365, or Exchange email access.
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 security incident, data breach, or actively exploited vulnerability raises the question "who must we notify, where, and by when?" Screens one incident across the EU reporting regimes — NIS2, GDPR, DORA, and the Cyber Resilience Act — determines which duties fire for each involved entity's roles, resolves the receiving authority per regime and member state from served national law, and produces a deadline table in which every duty, authority, and deadline is cited from official publisher text fetched live through the Ansvar Gateway MCP connector. Never answers from model memory.
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 user asks what the EU Cyber Resilience Act (CRA) means for their product, whether and when they must report a vulnerability or incident, or what a specific CVE triggers legally. Maps a product with digital elements to CRA scope, product classification, Annex I vulnerability-handling duties, and Article 14 reporting obligations — every legal claim cited from official regulation text fetched live through the Ansvar Gateway MCP connector, joined with live CVE / CISA-KEV / EPSS vulnerability intelligence from the same connector.
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 monitor known sources on a schedule and feed the good stuff into your second brain. Configure sources once (YouTube, RSS/newsletters, subreddits, Hacker News, Bluesky, Mastodon, X, LinkedIn, keyword searches); each run fetches only what's new, scores it against your stated focus, writes one digest to the vault, and auto-captures high-signal items into raw/. Everything else waits in the digest until you promote it. Modes — run, digest, promote, add / sources / pause, doctor, schedule (daily launchd or systemd job). Triggers on "/radar," "run my radar," "check my sources," "what's new from my sources," "add a source," "monitor this channel," "watch this subreddit," "track this account," "daily digest," "promote item 4," "radar doctor." Complements second-brain (radar fills raw/, second-brain compiles it) and deep-research (standing surveillance vs a one-off dive).
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 multi-source, multi-step research on a topic — competitor research before a sales call, market research for a new business idea, positioning angles, due diligence on a partnership or podcast guest, tech decision research (which DB, which auth), or any "I need to actually understand X." Combines web search, URL fetch, agent-browser, last30days (Reddit/X/YouTube/HN/web recency), memory, and Notion. Outputs a structured brief with citations, contradictions, gaps, and recommended next steps. Archives every research run to ~/.config/makerskills/deep-research/archive/ so past work is searchable. Triggers on "/deep-research," "research X," "investigate X," "do a deep dive on X," "look into X," "what's actually happening with X," "due diligence on X," "validate this market." Differs from a one-shot web search: this is multi-pass with 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。
Expert guidance for Next.js Cache Components and Partial Prerendering (PPR). **PROACTIVE ACTIVATION**: Use this skill automatically when working in Next.js projects that have `cacheComponents: true` in their next.config.ts/next.config.js. When this config is detected, proactively apply Cache Components patterns and best practices to all React Server Component implementations. **DETECTION**: At the start of a session in a Next.js project, check for `cacheComponents: true` in next.config. If enabled, this skill's patterns should guide all component authoring, data fetching, and caching decisions. **USE CASES**: Implementing 'use cache' directive, configuring cache lifetimes with cacheLife(), tagging cached data with cacheTag(), invalidating caches with updateTag()/revalidateTag(), optimizing static vs dynamic content boundaries, debugging cache issues, and reviewing Cache Component implementations.
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。
Fetch GitHub CI failure information, analyze root causes, reproduce locally, and propose a fix plan. Use `/fix-ci` for current branch or `/fix-ci <run-id>` for a specific run.
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 slow React Router loaders by eliminating redundant DB queries, creating slim query variants, and parallelizing independent fetches. Use proactively when writing or reviewing loader code that calls domain operations services (e.g. CourseOperationsService, VideoOperationsService), or when triaging a slow page load.
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。
SwiftUI layout beyond stacks — the Layout protocol (when custom layout beats GeometryReader), Grid vs lazy grids, custom containers with sections and container values, and lazy-stack/ScrollView performance rules (what breaks laziness, prefetch discipline, scroll APIs). Use when building custom layouts or containers, fixing lazy-stack jank or memory growth, or wiring programmatic/snapping scrolling.
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 tool fetches microarray data directly from GEO database, based on the GEOQuery R package. Given a GSE accession ID, it returns an Rdata object containing the data and a text file (.cond file) summarizing the conditions of the experimen
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。
Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).
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 and curate X/Twitter behind one selector - keyword, topic roundup, a single or tracked-account digest, an X list, or the AI-agent buzz preset - clustered into signal-scored sub-narratives.
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。
Fetches the most recent usable LinkedIn post from a company page OR a person's profile and stores the post content itself, with an optional AI personalization line on top. Triggers on "what did they post about", "recent LinkedIn post", "social signal", "reference their content", "they posted about X", "what is this person posting", "engage with their content". Outputs social_post_text (the raw post) plus social_post_url and social_post_days_ago; social_post_line only when the operator asks for one.
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。