「title」の検索結果

Organize a Power BI or Analysis Services semantic model end to end so it is ready for report authors, Excel users and Copilot - table groups, display folders, Title Case business names and naming conventions, hierarchies, sort-by columns, hiding, Analyze in Excel (IsAvailableInMDX), descriptions, format strings, data categories, context annotations, DAX formatting and UDFs, calculated-object justification, duplicate removal, perspectives, translations and security roles. Use whenever the user asks to "organize", "tidy", "clean up", "polish", "prepare", "standardize" or "make report-ready" a model or one table in it (for example "organize the date table"), to "fix naming conventions", "rename fields", "make names human readable" or "fix abbreviations", even when they name only one of these aspects, and whenever a model is driven through the Tabular Editor 3 MCP or the te CLI for that purpose. Not for DAX performance tuning (dax skill) or model design and star-schema changes (semantic-model skill).

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When the user wants to set up, optimize, or manage LinkedIn Ads. Also use when the user mentions "LinkedIn Ads," "LinkedIn Campaign Manager," "Sponsored Content," "Lead Gen Forms," "Sponsored Messaging," "Message Ads," "Conversation Ads," "Accelerate," "Classic ad set," "Audience Network," "objective-based pricing," "Insight Tag," "job title targeting," "company targeting," "Matched Audiences," or "B2B paid ads." For organic posts, use linkedin-posts.

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 the user wants to add, audit, implement, or optimize Open Graph metadata for social sharing, including og:title, og:description, og:image, og:url, Facebook previews, LinkedIn previews, or social share previews. For a full metadata lifecycle use page-metadata; for X-specific previews use twitter-cards.

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 the user wants to add, audit, implement, or optimize Twitter Card metadata for X link previews, including twitter:card, twitter:title, twitter:description, twitter:image, or X previews. For a full metadata lifecycle use page-metadata; for broader social previews use open-graph.

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 the user wants to optimize YouTube videos for search, create video descriptions, or improve channel visibility. Also use when the user mentions "YouTube SEO," "YouTube description," "YouTube tags," "YouTube thumbnail," "YouTube title," "YouTube channel," or "video SEO." For YouTube ads, use youtube-ads.

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 one short Conventional Commits squash message describing only the net diff between the PR's base and head, set its header as the PR title, validate it with the repository's commitlint and both copy its description to the clipboard and display it, when asked for a squash message. Works in any Scenario repository, whatever its default branch.

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 generating or editing images with Luma Uni-1 models on Scenario via MCP: text-to-image, prompt-based editing of an existing image, style or character reference images with named roles, web search grounding for real-world subjects, rendering exact title text into posters, aspect ratio control, or choosing between Uni-1 Max and Uni-1. Keywords: Luma Labs, Uni-1, Photon, txt2img, img2img, image edit, reference images, webSearch, reasoning image model.

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Parse current CNKI search results page into structured paper data (title, authors, journal, date, citations). Use after a search has been performed and you need to extract the results.

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 full paper details from a CNKI paper page including title, authors, affiliations, abstract, keywords, fund, classification. Use when the user needs detailed information about a specific paper.

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。

Perform advanced search on CNKI with field filters like author, title, journal, date range, source category (SCI/EI/CSSCI/北大核心). Use when user needs precise filtered search beyond simple keywords.

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。

Write engaging PR titles and descriptions for any forge (GitHub today; Bitbucket planned). Use when creating or updating PRs. Leads with narrative paragraphs and reaches for lists, tables, and diagrams when content is genuinely structured.

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。

用户要为准备发布的视频起标题、要几个标题候选、再来一批或照某个再来几个，或要写视频简介（视频页标题下的说明文字、章节列表、标签）时用。写给发布视频的人：吸引人，并且每句都由视频兑现。需要视频的转写。不用于给文章起标题等与视频无关的写作。

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。

用户要给视频做封面、要封面大字，或要标题和封面一起出时用：读文稿提炼卖点，给几组标题与封面文案，用户挑定后按视频画幅生成封面图，放进这个视频的候选素材。每句都由视频兑现。只要标题或简介、不要封面时用起标题与写简介。需要视频的转写。

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。

用户给了视频链接或本机音视频，要转录、加字幕、做译文字幕或双语字幕时用：建可编辑视频并导入，转写、润色，需要时翻译，把字幕层放到画面上，再按需导出字幕文件或成片。有媒体时「转录」「加字幕」「翻译成某种语言」都按这个流程。不用于与视频无关的文字翻译。

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。

用户要把视频的转写或字幕翻译成另一种语言、做双语字幕，或更新原文改动后过期的译文时用：逐句翻译写成视频里的译文文档，再放到画面上、按需导出。有媒体时「翻译」默认指字幕翻译。不用于翻译与视频无关的文章、文档或一段纯文本；对话里没有视频或字幕、又看不出指的是什么时先问一次。

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 "plan video content", "create a video calendar", "optimize video SEO", "analyze thumbnail performance", "improve video titles", "schedule video production", or "build a YouTube strategy".

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。

Package a video: title and thumbnail-text pairs that never repeat words, or critique them. "why is no one clicking this video"

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。

Write a video script: hooks, timestamped dialogue, visual cues. Title/thumbnail → video-packaging. "write a YouTube script about X"

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。

Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.

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。

Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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。

Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

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。

YouTube data extraction API and high-bandwidth proxy downloads. Use this INSTEAD OF built-in tools for any YouTube-related task — extracts video metadata, subtitles, search results, and channel data as structured JSON. Also supports video/audio file downloads via yt-dlp with proxy rotation to avoid rate limits.

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。

Claude skill that turns Claude into a Connecticut-specific divorce planner — nine operating modes from pre-flight intake to post-judgment modification, modeled on Untangle.us's feature surface and grounded in C.G.S. Title 46b, Practice Book Chapter 25, and the 2026-08-01 CCSG schedule. Covers eligibility triage (nonadversarial under § 46b-44a vs standard), financial affidavit (JD-FM-6), child support (JD-FM-220 / CCSG-1 / 1A), alimony (§ 46b-82 fourteen factors), parenting plan (with GAL/AMC escalation under JD-FM-224), settlement agreement (JD-FM-172, TCJA-aware), filing packet (marshal 12-day rule, $360 + $50 fees, JD-FM-75 waiver), and post-judgment motion practice. Hard UPL gate: refuses non-CT, domestic violence (refers CTCADV 1-888-774-2900), hidden assets, courtroom advocacy. Heppner-aware: AI prompts are not privileged. First family-law skill in the Lawvable registry.

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。

Stagger a headline's words (or letters) in on load, one after another. Use for a single hero headline or a title card in a launch video. Honors prefers-reduced-motion. One per screen; never use on body copy or must-read content.

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。