853 件 ・ 関連度順
概要と使いどころ
Generates the "Results" section for meta-analysis sensitivity analysis based on statistical tables and titles. Use when the user wants to describe sensitivity analysis results or format sensitivity tables for a meta-analysis paper.
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Generates structured biomedical outlines for review articles, discussion sections, and thesis proposals. Use when a user provides biomedical keywords, results/discussion text, or a proposal title plus background and needs a directly usable academic writing scaffold.
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。
Generates a first draft of a clinical meta-analysis paper. Input the research report (including Methods and Results sections), language, and title to automatically generate a complete paper draft including Abstract, Introduction, Discussion, and other sections, with automatic ...
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EndNote reference formatting workflow — converts [PMID: xxxx] markers in Markdown manuscripts to Word (.docx) using EndNote CWYW-recognized {Author, Year, Title} placeholders, while generating .ris files for automatic import into the local EndNote library. Users click "Update ...
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。
A medical-research-native literature reading skill for users with clinical, bioinformatics, translational, and basic experimental backgrounds. Use this skill whenever a user wants to read, analyze, critique, or interpret a medical or scientific paper — whether they provide a PDF, abstract, DOI, PMID, or just a title. Triggers include requests like \"analyze this paper\", \"critique this study\", \"is this a strong paper?\", \"give me similar studies\", \"prepare me for journal club\", \"help me understand this bioinformatics paper\", \"what are the weaknesses here?\", or \"turn this into a mind map\". Also activate for any downstream deliverables such as journal club kits, comparison tables, PI decision briefs, replication starters, or follow-up experiment designs. Do NOT treat as a generic summarizer — this skill performs structured evidence-type classification, track-specific critical appraisal, interpretation-boundary judgment, and research-grade follow-up generation.
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Reverse-engineers the methods section of a biomedical paper into a structured, reproducible workflow. Use this skill when a user wants to understand how a study was actually executed, extract data sources, inclusion/exclusion logic, preprocessing, analytical sequence, software/tools, validation path, and critical parameters, or build a replication checklist from a paper, abstract, DOI, PMID, title, screenshot, or partial methods text. Do not treat this as generic summarization. Focus on reconstructing the operational method pipeline, surfacing missing reproducibility details, and distinguishing explicitly reported steps from inferred or unresolved ones. Never fabricate references, methods details, identifiers, software versions, parameters, datasets, or validation steps.
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。
Collects candidate biomedical literature across multiple databases, adapts search logic by database, preserves source metadata, and organizes results into a structured, screening-ready candidate pool. Always use this skill when a user wants cross-database literature collection, search strategy construction, candidate paper aggregation, or first-pass evidence organization before deduplication, screening, layered reading, or review planning. Requires real and verifiable literature records only. Every formal literature item must include a real link and DOI when available; never fabricate citations, titles, authors, years, journals, abstracts, PMIDs, or DOIs. If a DOI is unavailable or cannot be verified, state that explicitly rather than inventing 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。
Reorganizes a paper into a storyline suitable for scientific posters. Use when planning the section structure, title hierarchy, figure selection, and live-explanation flow for an academic conference poster. Also triggers on "help me design a poster layout", "what sections should my poster have", "how do I arrange my poster", "poster structure for [conference]", or "which figures should I use for my poster".
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。
Checks consistency across title, abstract, methods, results, figures, tables, and supplements to identify internal contradictions and version drift in biomedical manuscripts.
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。
Detect initial silence segments in audio/video using energy-based analysis. Use when you need to find low-energy periods at the start of recordings (title slides, setup time, pre-roll silence).
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Transcribe audio segments to text using Whisper models. Use larger models (small, base, medium, large-v3) for better accuracy, or faster-whisper for optimized performance. Always align transcription timestamps with diarization segments for accurate speaker-labeled subtitles.
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 optimized meta titles, descriptions, and URL suggestions based on character limits and best practices. Generates compelling, keyword-rich metadata. Use PROACTIVELY for new content.
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Premise, theme, controlling idea, subject selection and logline for scripts (前提/主题/立意/选材/戏核) — merged from Lajos Egri's premise-as-tyrant and dialectic, Robert McKee's controlling idea (value + cause) and idea/counter-idea, Neill Hicks' five premise questions, Lisa Cron's "third rail" (desire vs misbelief, origin scene, what-if), Julian Hoxter's logline and theme-attitude rule, Blake Snyder's logline/genre/title tests, and Lu Jun's Chinese craft chapters on 选材要严/开掘要深/视角要新/戏核要好/情节要奇. Use when turning a vague idea into a premise, finding what a story is really about, choosing a subject and angle, testing a logline, deciding the ending from the theme, or diagnosing a script that "has events but no story".
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科技/AI/互联网领域的公众号 10 万+ 爆款标题生成器。输入一篇文章、一段内容或一个主题，先建内容简报，再按多种方法产出多个候选标题，逐个评分、标风险、按用途分角色推荐，并给 A/B 测试建议。当用户说"起标题""想个爆款标题""这篇文章叫什么好""标题优化""标题改写""多组标题""标题评分""10万+标题"时触发。方法论提炼自 100 篇真实科技类爆文标题。
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。
小红书笔记正文撰写。输入主题/产品/经历/素材，产出可直接发布的小红书正文（含开头 3 行、分段骨架、结尾互动、标签组合、合规自检）。覆盖种草测评、干货教程、个人故事、合集清单、避雷拔草、好物分享、经验复盘 7 种笔记类型。当用户说"写小红书""小红书文案""发笔记""笔记正文""种草文""种草笔记""避雷帖""干货笔记""帮我写篇小红书""这个怎么发小红书""小红书怎么写""笔记体检""改成小红书风格"时触发。标题批量生成交给 space-xhs-title，封面/配图交给 xhs-html。
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。
小红书爆款标题生成器。输入一个主题、一篇笔记草稿，或一条现成标题，先建内容简报，再按小红书特有的 15 种标题方法批量产出候选，逐条评分（含搜索词覆盖、人群指向性、收藏动机）、标合规风险、按用途分角色推荐，并给 A/B 测试建议。当用户说"小红书标题""起个笔记标题""帮我想小红书爆款标题""这条笔记叫什么好""标题优化/改写""标题没人点""怎么让人搜到我""标题评分"时触发。区别于公众号标题：更短、更口语、强搜索、强人群标签、emoji 标配。
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 and analyze WeChat Official Account hot articles / 公众号爆款文章 by sector or keywords. Use when the user asks for 爆款文章分析, 赛道爆款, 公众号爆款数据, reading counts, likes, shares, comments, title patterns, writing style, 爆款原因分析, or writing references for content creation.
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 cloned narration for the content workspace. Use local IndexTTS2 with the canonical lossless Pluviobyte reference for every local video, voice audition, digital-human narration, and subtitle-ready audio render. Preserve MiniMax only for public-facing articles or tutorials that teach users to connect through the relay service; never use MiniMax for local video production.
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。
Edit any video by conversation. Transcribe, cut, color grade, generate overlay animations, burn subtitles — for talking heads, montages, tutorials, travel, interviews. No presets, no menus. Ask questions, confirm the plan, execute, iterate, persist. Production-correctness rules are hard; everything else is artistic freedom.
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。
口播基础素材包生成。转录口播、识别口误、生成审核页；用户确认后剪出新视频，Agent 再基于剪后视频重新转写、AI 校对字幕，输出后续口播成片可用的 source_cut.mp4 和 subtitles.srt。触发词：剪口播、处理口播素材、准备口播素材、识别口误、基础素材包
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 reusable black-background white-text opening animations for new videos. Use when the user asks for "黑底白字开场", "纯黑加白字", "白色文字逐渐出来", "一个个字出来", "打字效果", "打字音效", "字体变化开头", "opening title animation", "kinetic text opener", or a short black-and-white intro before a HyperFrames, Remotion, ffmpeg, SaaS/product, tutorial, commentary, or course video. This is for original opener creation, not pixel-level reference matching.
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 and composite HeyGen digital-human videos in the content workspace. Use whenever the user asks for a 数字人, 数字人5, HeyGen, AI 口播人物, 数字人小窗, 圆形头像口播, full-screen digital human, or asks to make a video that uses the existing avatar. Enforce Creator-plan CLI OAuth, the configured Digital Twin, local IndexTTS2 narration, Avatar III for an unspecified digital human but Avatar V whenever the named preset 数字人5 is requested, adaptive face measurement plus the approved human-reviewed visual-centering offset in the headroom_08 circular bottom-left layout unless full-screen is explicitly requested, subtitle-safe placement, credit-aware master reuse, final QC/archive routing, and mandatory pairing with `heygen-avatar-motion` before any motion prompt or paid generation.
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。
Produce a polished local talking-head or narrated screen-recording rough cut without a cloud editor. Use when Codex must clean Chinese or mixed Chinese-English speech, correct product terminology before semantic editing, compress pauses without making speech breathless, preserve source resolution and frame rate, normalize dialogue loudness, generate final-audio subtitle artifacts, or benchmark local output against ChatCut/video-use/chengfeng/AI剪口播.
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Fetches real, citable Bilibili (B站) video data — stats, metadata, tags, and full danmaku text — via login-free API calls, never hand-typed or estimated. Use when citing view/like/favorite counts, analyzing why a video performed, or archiving a Bilibili source into a knowledge base. Accepts BVID, av numbers, b23.tv links, or full URLs; subtitles and 收藏夹 (favorites) enumeration need the user's Bilibili login.
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。