409 件 ・ 関連度順
概要と使いどころ
Routes tasks for discovering NLP datasets in the CLUEDatasetSearch catalogue, including Chinese NLP classification, QA, matching, NER, generation, translation, corpus, and reading-comprehension resources.
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 jadore801120 attention-is-all-you-need-pytorch for Transformer architecture inspection, preprocessing, training, and checkpoint translation workflows.
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。
Routes Argos Translate workflows for offline machine translation, package installation, CLI usage, runtime settings, and troubleshooting.
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。
检查文稿里的 AI 味和账号语气偏差，包括机器化表达、翻译腔、虚构脆弱感和过度金句。用户问文案是否像 AI 写的、是否像本人说话，或希望降低 AI 痕迹时使用。 English: Check drafts for AI-writing signals and voice mismatch, including robotic phrasing, translation-like prose, fabricated vulnerability, and forced quotable lines. Use when the user wants the copy to sound more human or more like the target account.
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 "make an audiobook", "narration script", "narrator", "ACX", "Findaway", "pronunciation guide", "how long is the audiobook", "adapt to a screenplay", "Fountain", "screenplay", "picture book", "spreads", "illustration notes", "art notes", "comic script", "comics script", "graphic novel", "panels", "interactive edition", "turn the book into Ink or Twine", "translate the book", "translation", "foreign edition", "glossary for translators", or wants to turn a story project into another form or language, or to plan a picture book. NOT for writing a new branching or choose-your-own-adventure story (use interactive-fiction), or writing rhyming picture-book text (use verse-craft).
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。
Translate video subtitles (SRT, VTT, TXT) between languages. Supports batch translation and maintains timing synchronization. Use when creating multilingual subtitles, expanding to international audiences, or translating video transcripts.
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。
Apply the bioengineering, translational systems biology, and tissue modeling frameworks of Linda Griffith, Professor of Biological Engineering at MIT and tissue engineering pioneer. Use this skill whenever facing decisions, designs, or evaluations in bioengineering, tissue modeling, microphysiological systems (organs-on-chips), synthetic matrix design, disease subtyping, or drug target validation. Reach for this skill when evaluating preclinical models (human vs. animal), reframing overlooked or neglected pathologies into rigorous engineering challenges, selecting biomaterials, designing cell signal processing assays, or diagnosing operational flaws in experimental platforms (e.g., PDMS compound absorption or Matrigel lot variability).
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 self-contained, beautifully styled HTML analysis of an academic paper. Use when the user provides an arXiv link, paper URL, PDF, or asks to analyze a research paper. Produces a standalone HTML file with structured sections (Problem, Translation/Analogy, Architecture, Key Results, Verdict), embedded figures, and responsive design. Trigger words include 读论文, 分析论文, paper analysis, paper review.
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。
Automatically translate and sync App Store metadata (description, keywords, what's new, subtitle) to multiple languages using LLM translation and asc CLI. Use when asked to localize an app's App Store listing, translate app descriptions, or add new languages to App Store Connect.
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。
Implements multi-language support using i18next, gettext, or Intl API with translation workflows and RTL support. Use when building multilingual applications, handling date/currency formatting, or supporting right-to-left languages.
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。
iFlytek Machine Translation (机器翻译) — translate text between Chinese, English, Japanese, Korean, French, Spanish, German, Russian, Arabic, Thai, Vietnamese, and many more languages. Use when the user wants to translate text. Pure Python stdlib, no pip dependencies.
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。
Systematic trade idea generation framework, fundamental quantitative and qualitative screening pipeline, catalyst-driven trade structuring, macro-to-micro idea translation, 20-60 day long-short portfolio management process
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。
Think and work like an expert Comparative Medicine Researcher. Use when a task calls for Comparative Medicine Researcher judgment. Reasons from species biology, translational validity, and the 3Rs through model-validity frameworks, IACUC protocols, ARRIVE 2.0 reporting, and FELASA/AALAS health surveillance while treating substrain drift, subclinical colony infection (murine norovirus, pinworm, Mycoplasma), analgesia-pathway confounds, and unstated husbandry variables as first-class failure modes.
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。
Translate text content between languages with high quality and natural phrasing. Covers document translation, content localization, and multi-language research support for teams working across language barriers.
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 and understand audio with OpenAI request-based audio APIs and audio-capable chat models, including text-to-speech, transcription, translation, multimodal audio input/output, model routing, prompt and performance direction, artifact custody, approval gates, and safety/rights review. Use for non-realtime OpenAI audio production; route continuous live voice agents to the separate realtime voice skill.
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 this skill when an agent needs AssemblyAI for speech-to-text or speech-understanding work in media production, including pre-recorded, synchronous short-file, and real-time streaming transcription; speaker diarization or speaker identification; captions and subtitles; timestamps; language detection, code-switching, or transcript translation; audio intelligence such as summaries, chapters, topics, entities, key phrases, sentiment, content moderation, profanity filtering, and PII redaction; webhooks, scaling, rate limits, retention, security, consent, and QA for podcasts, interviews, captions, call recordings, and edit workflows.
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 Microsoft Azure Speech in Foundry Tools for media-production speech workflows: speech-to-text, fast and batch transcription, diarization, captions/subtitles, real-time transcription, text-to-speech neural and HD voices, SSML, custom/personal voices, text-to-speech avatars, speech/video translation, localization, quotas, regions, privacy, consent, rights, and production QA.
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 NVIDIA Speech NIM microservices for speech production and voice workflows, including self-hosted ASR/STT, TTS, text translation, speech-to-speech pipeline design, Riva Python client integration, deployment planning, GPU/runtime sizing, licensing/privacy review, and production QA for transcription, captioning, voice agents, localization, and synthetic voice output.
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。
Provider-independent cinematic trailer production for AI agents creating movie-style trailers, teaser trailers, launch trailers, game trailers, documentary trailers, series promos, and high-impact generated-media previews. Use for trailer strategy, structure, shot planning, voiceover/title-card copy, music and sound-design direction, generated-video prompt translation, edit pacing, platform/runtime choices, delivery handoff, rights/claims caveats, and trailer QA.
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。
Provider-independent production guidance for AI agents creating or retouching appetizing food and beverage images, recipe videos, restaurant/menu visuals, CPG ads, ecommerce product images, beverage pours, packaging/lifestyle shots, and social food clips, including truthfulness, labeling/claims discipline, styling, prompt translation, platform variants, accessibility, rights, alcohol, and QA.
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。
Provider-independent localization and dubbing production direction for AI agents producing translated videos, dubbed ads, social clips, explainers, avatar videos, documentaries, training media, and multi-market campaigns. Use when planning or reviewing subtitle-versus-dub strategy, translation adaptation, glossary/style-guide setup, casting or voice matching, lip-sync or phrase-sync direction, synthetic dubbing boundaries, captions/subtitles handoff, accessibility, platform delivery, client review, or localization QA.
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。
Workflow for ribosome profiling, P-site aware preprocessing, periodicity checks, ORF detection, and translation efficiency analysis.
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 DNA/RNA/protein sequences. Use when the user provides a sequence and asks for analysis, translation, GC content, ORFs, motifs, restriction sites, or primer design. Triggers on "sequence", "translate", "GC content", "ORF", "primer", "restriction", "complement", "reverse complement".
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。
Native agent-to-agent language for compact multi-agent messaging. A shared tongue agents speak directly, not a translation layer. 340+ atoms across 7 domains; 3x smaller than natural language.
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。