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概要と使いどころ
Use when revising an ACM MM (ACM Multimedia) paper for house style — putting the cross-modal contribution on the first page, framing media (figures, video, audio) as evidence rather than decoration, making the fusion the visible claim, and compressing the argument into a 6-8 page ACM sigconf body with references-only overflow.
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 organizing appendices and supplementary material for an ACL paper under ACL Rolling Review, covering the mandatory Limitations and optional ethics sections, appendices after references, anonymized software and data archives, the no-cloud-links rule, and deciding what must stay in the 8-page or 4-page body.
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 revising an ACL paper for computational-linguistics house style, covering task-first framing, linguistic examples tied to quantitative error analysis, scoping language claims to tested languages, LLM-era claim discipline, anonymous self-reference, Limitations prose, and compressing into the 8-page or 4-page ACL format.
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 preparing an accepted AAAI paper for camera-ready source submission to AAAI Press, including proceedings page limits, two-column template compliance, copyright transfer, purchased extra technical pages, deanonymization, registration, oral or poster presentation, and final public artifact release.
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 revising an AAMAS paper so the interaction contribution leads the first page, the solution concept or incentive property is named, the game and agents are legible, claims are paired with proofs or multiagent experiments, the argument fits eight two-column pages plus references, and the wording stays double-blind.
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 auditing an AAMAS main-track submission for OpenReview readiness, the 8-page-plus-references limit, the full-paper versus 2-page extended-abstract choice, double-blind anonymity, the supplementary zip cap, track fit across the AAAI/JAAMAS/Blue Sky tracks, dual-submission rules, and desk-reject triggers before upload.
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。
Pull real SEO metrics for any domain using Apify scrapers for Semrush and Ahrefs data. Gets domain authority, organic traffic estimates, keyword rankings, backlink profiles, top performing pages, and auto-discovers competitors from keyword overlap. No Semrush/Ahrefs subscription needed — uses Apify actors that scrape public pages.
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。
Identify programmatic SEO page patterns worth building for your product — vs/ pages, integrations/, for-{industry}/, alternatives-to/, use-cases/ — and design the template structure, data model, and priority order. Outputs a complete pSEO blueprint with URL patterns, title templates, content frameworks, and data sources per variable.
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。
Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.
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 structured data from web pages using AI
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 competitor and customer intelligence from any company's landing page HTML. Discovers tech stack, analytics tools, ad pixels, customer logos, SEO metadata, CTAs, hidden elements, and more. No API keys required.
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。
Assemble a narrated-UGC "stitch reply" ad from a config — a single spoken VO carries a verbatim testimonial while ~30 per-cut i2v clips (one creator across ~5 wardrobes in ~3 worlds, plus product B-roll) are each trimmed to their EDL window built from the VO's Whisper word boundaries and hard-concatenated via filter_complex concat (never the demuxer, which drops audio on a duration mismatch), the VO mixed over an optional sidechain-ducked instrumental bed (−20dB, 20 to 1) so the VO stays on top, karaoke-pop captions burned on every word throughout (VEED Whisper preset, re-spelled against the locked script), a landing-page scroll rendered as FFmpeg zoompan over a Playwright PNG (not i2v), and closed on the brand's real end-card PNG — never AI-rendered text. This is the FREE deterministic assembly stage (trim-to-EDL + filter_complex concat + VO and music mix + karaoke captions + landing-page zoompan + end-card append), run with the shared stitch-videos-ffmpeg montage.py helper that installs with this package; the VO, creator, start-frames, and clips come from create-vo-elevenlabs / create-image-gpt-image-fal / create-image-fal / create-video-fal. Use for the narrated-ugc-wardrobe-stitch format.
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。
Plan, design, author, preview, publish, and manage Power BI reports across requirements, page design, local PBIR/PBIP edits, validation, screenshots, Fabric upload/download, and rebinding. Use for report lifecycle work; use semantic-model-authoring for model or DAX changes and fabriciq for data questions. Triggers: plan Power BI report, design report page, edit PBIR, preview PBIP, publish report, rebind 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。
Compare two or more companies, products, or platforms across pricing, features, positioning, and docs. Use this skill whenever the user says "compare X vs Y", "how does X stack up against Y", "alternatives to X", "competitive landscape of …", "X vs Y vs Z", or asks for a competitor matrix. Uses search to discover competitors when the user only names a category, then scrape for each competitor's homepage, pricing page, and features/docs. Returns a normalized comparison matrix as JSON.
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 and normalize pricing tiers from any SaaS, API, cloud, or LLM vendor's pricing page. Use this skill whenever the user says "pricing for X", "how much does X cost", "pricing tiers", "cost comparison", provides a URL ending in `/pricing` or `/plans`, or asks to monitor pricing over time. Pairs well with `exportSkill` to turn a run into a cron-friendly workflow. Scrape-driven; no interact needed for typical pricing pages.
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。
Prove the next page of a list, or the next batch of an infinite scroll, loads NEW rows from the server, repeats none, and that the end of the list is handled. Use when pagination or infinite scroll was added or changed, when a list shows the same rows twice or skips some, or when the last page still offers a next control.
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。
Embeds and controls web content in SwiftUI with WebKit for SwiftUI, including WebView, WebPage, navigation policies, JavaScript execution, observable page state, link interception, local HTML or data loading, and custom URL schemes. Use when building iOS 26+ article/detail views, help centers, in-app documentation, or other embedded web experiences backed by HTML, CSS, and JavaScript.
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 Viking web projects, start and verify a local preview, or deploy a generated project to Volcengine IGA Pages when explicitly requested. Includes agent-guided feature, eligible application, dataset, scene, and authentication choices. Use only after confirming the installed CLI exposes `vs project`; otherwise stop without taking action.
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 planning many similar pages from a template and a data set: choosing the pattern, deciding whether the data can carry it, and avoiding the thin-content failure that gets page sets deindexed.
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 reviewing a page or site for organic search, or diagnosing why something isn't ranking: crawl and index signals, on-page elements, content quality, and how to order the fixes.
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。
Build and validate experimental WebMCP tools for an existing web page. Use when an agent needs to expose a site's real workflows as page tools, create webmcp.init.js, define deterministic checks, or compare WebMCP with accessibility-tree automation.
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。
Deploy static sites and full-stack apps on Cloudflare Pages with previews, functions, and custom domains.
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 driving a web page in a browser — clicking, typing, navigating, logged-in or JS-rendered pages. Jev picks each step from the elements observed, under a host allowlist and a step budget.
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。
Answer a question from a second-brain vault by reading its own pages, citing the pages used, and saying plainly when the vault does not contain the answer. Use this skill whenever the user asks what they know about a topic, what they have read on something, what connects two ideas, what they have changed their mind about, or asks any question that should be answered from their own notes rather than general knowledge. Do NOT use for ingesting new material, for general questions the vault has nothing to do with, or when the user explicitly wants an answer from the open web.
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。