「vocabulary」の検索結果

Searches the domestic courts of 122 jurisdictions — 153 databases, 49 automated — for extradition and arrest-warrant surrender decisions, each in its own language and vocabulary. Answers the question no commercial database does: how are OTHER executing states treating this requesting state, or this ground? Searching by requesting state localises its name per jurisdiction (AE becomes 'Emiratele Arabe Unite' in Romania, 'Emirati Arabi Uniti' in Italy), so the sweep finds what those courts actually wrote. Every hit passes a relevance gate; every search leaves a dated report, so the research is reconstructable months later. Use when asked what foreign courts have said about surrender to a given state, whether any European court has refused extradition on prison conditions, assurances or Article 3, for comparative extradition research, or to build a foreign-authority section of an extradition argument. Not for domestic case law of the user's own jurisdiction, and never a substitute for reading the judgment.

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Analyse text complexity across quantitative, qualitative, and reader-task dimensions with scaffolding recommendations. Use when selecting texts, assessing readability, or planning reading support.

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Classify a console screen (list/record/form), build it on @temps-sdk/ds templates and the shared shadcn primitives in @temps-sdk/ui, and follow the console's status vocabulary and status colour rules. Use for any new or changed console UI in web/src, and when building or extending web/packages/ds itself.

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Infrastructure to support 'views' used to classify Bioconductor packages. 'biocViews' are directed acyclic graphs of terms from a controlled vocabulary. There are three major classifications, corresponding to 'software', 'annotation', and '

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Game feel ("juice") for Apple apps — celebration choreography, haptic vocabulary design, sound-effect layers, and the event×channel feedback audit. Use when big moments fall flat, when designing haptics or SFX, or when auditing whether every meaningful event actually reaches the user.

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SF Symbols end-to-end — choosing and configuring the 7,000+ system symbols (rendering modes, variable color/draw, gradients), authoring custom symbols that interpolate across weights, and the animation preset vocabulary. Use when picking iconography, building custom symbols, animating symbol state changes, or rendering values as symbols.

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

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Define a brand's verbal identity — tone, voice, writing style, vocabulary, and messaging rules. Use when the user says "brand voice", "tone of voice", "how should we write", "writing guidelines", "copy style guide", "brand language", "verbal identity", "how should the brand sound", "tone guide", "our copy doesn't sound right", "copywriter guidelines", "voice and tone", or when onboarding a copywriter or content team. Also use when the user has a brand strategy and wants to define how the brand communicates.

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Use when the user needs to define, document, or enforce how the brand SOUNDS in writing — three personality traits, a five-dimension tone table, vocabulary to use, avoid, and ban, sentence rules, before and after rewrites, platform adaptation, and a copy approval checklist. Every content skill reads it before writing. Trigger on 'brand voice', 'tone of voice', 'voice guidelines', 'banned words list', 'this copy does not sound like us', 'every writer sounds different'. Also use when the user cannot say why a draft feels wrong. Not for — the visual side of brand, see `46-brand-guideline-global`; positioning and the message, see `58-positioning-global`; approving one specific piece, see `62-marketing-review-global`.

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针对给定的英语单词，提供中文释义，并使用《小猪佩奇》的简单词汇水平生成3个非对话形式的英文陈述句。

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Sets up an `## Agent skills` block in AGENTS.md/CLAUDE.md and `docs/agents/` so the engineering skills know this repo's issue tracker (GitHub or local markdown), triage label vocabulary, and domain doc layout. Run before first use of `to-issues`, `to-prd`, `triage`, `diagnose`, `tdd`, `improve-codebase-architecture`, or `zoom-out` — or if those skills appear to be missing context about the issue tracker, triage labels, or domain docs.

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Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.

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。

Remove AI writing patterns from academic prose. Detects and fixes inflated symbolism, promotional language, superficial analyses, vague attributions, AI vocabulary, and formulaic structures. Supports English and Chinese. Triggers on "remove AI patterns", "humanize text", "anti-AI polish", "去除AI写作痕迹", "人性化处理".

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Produces human-sounding text that avoids detectable AI writing patterns. Activates on any writing task — tweets, emails, articles, bios, captions, reports, copy, messages, LinkedIn posts, cover letters, README files, or any content where the output must not read as AI-generated. Enforces banned vocabulary, structural variety, punctuation discipline, accuracy rules, and voice calibration. Use when the user says "write," "draft," "rewrite," "make this sound human," "anti-slop," "not AI," or any variation of wanting authentic-sounding output.

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Use whenever the user asks to "humanize", "make this sound more human", "rewrite to avoid AI detection", "make this less AI-sounding", "add a human voice", or "write like a person". Also use when the user pastes text and asks why it reads as robotic, generic, flat, or AI-like, or when generating new text in a register where AI tells (em dashes, semicolons, hedges, banned vocabulary like "delve", "leverage", "robust") would damage credibility.

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Film and video storyboarding with shot vocabulary, continuity rules, and panel layout. Covers shot types, camera angles, movement, 180-degree rule, and annotation format. Use for: video planning, film pre-production, ad storyboards, music video planning, animation. Triggers: storyboard, storyboarding, shot list, film planning, video planning, pre production, shot composition, camera angles, scene planning, visual script, animatic, storyboard panels, video storyboard

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Remove the AI tells readers react to in an Instagram caption or carousel slide: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, emoji storms; caps em dashes. Includes --mode audit (first-125 hook, length, hashtags, emoji, CTA, media) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use ig-caption-writer or ig-carousel-planner). Keywords: humanize, de-AI caption, audit before posting.

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Reference for writing and editing skills well — the vocabulary and principles that make a skill predictable.

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Configure this repo for the engineering skills: set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

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Alias for domain-modeling. Use when the user asks for domain modeling, ubiquitous language, domain terminology, glossary work, or DDD vocabulary.

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Reverse-lookup glossary that turns a vague description of a web animation or motion effect into its exact term ("the bouncy thing when a popover opens" → Pop in; "the iOS rubber-band scroll" → Rubber-banding). Use when the user asks "what's it called when…", or describes a motion effect without knowing its name and wants the right word to prompt an AI or designer with. For naming an effect, not designing or building 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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

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 writing a complete SEO article. Includes the full anti-AI-slop ruleset (banned vocabulary, banned phrases, banned structural patterns) and voice rules. The agent researches the SERP itself if needed — no keyword data exports required.

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Analyzes a company's content to extract and codify their brand voice into a comprehensive style guide. Reads website copy, blog posts, emails, and social media to identify tone, vocabulary patterns, sentence structure, personality traits, and word preferences. Generates a brand-voice-guide.md and reviews new content against it.

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。