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Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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Generate AI-friendly repository documentation with the SourceSage CLI. Use when Codex needs to run `sage` or `sourcesage` to create `.SourceSageAssets/Repository_summary.md`, analyze the current repository or another local repository, switch the output language between English and Japanese, use `--lite` to keep the summary small, change the output directory, or optionally create a deprecated tag-diff release report with `--diff`.

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Find academic papers across up to 8 sources (OpenAlex / Semantic Scholar / CrossRef / PubMed / arXiv for English, OpenReview for AI venues, plus native-Chinese retrieval via NSSD 国家哲社文献中心 + yiigle 中华医学期刊) with adjustable depth — Quick scan (5 min) to Audit prep (3 hr). Use when the user wants to find papers, run a literature search, gather references, scope a research topic, search Chinese-language / 中文原生 literature (中文文献/中文核心/CSSCI/C刊/国内研究/国内文献/中华××期刊/心理学报/经济研究), or filter results by journal tier (中科院分区/一区/几区, Q1, JCR/SJR quartile, 影响因子/impact factor, 期刊分区, 顶刊/top journal, '按分区筛'), or export paste-ready professional search strategies / 检索式 for external databases (PubMed / WOS / Scopus / Embase / 知网 CNKI / 万方 / SinoMed — '写检索式', '导出检索式', 'WOS 检索式', '知网专业检索', 'search strategy', 'boolean search strategy'). Triggers on search verbs ('find papers', 'literature search', 'papers about X'), review types ('scoping review', 'systematic review', 'SR prep', 'literature review', 'lit review', 'help me write a lit review'), Chinese ('找文献', '找论文', '论文搜索', '学术检索', '文献检索', '文献综述', '综述前期', '求文献', '中文文献', '中文核心', 'CSSCI', 'C刊', '国内研究', '找中文的'). Outputs Shadcn HTML report + BibTeX/RIS/CSV + PRISMA-S log. Do NOT use for: concept explanations ('what is X' / 'X 是什么', e.g. '影响因子怎么算'), writing ('帮我写' / 'help me write a paragraph'), single-paper interpretation or PDF download with metadata (use paper-downloader-portable), or when the user already has a literature set (use literature-set-review).

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Use when the user wants to create/generate/scaffold a new Spring Boot project (Maven or Gradle, REST API / Web App / Spring Boot + Angular full stack). Derives progen CLI inputs from the user's plain-English project description, asks for any missing mandatory info, ensures the progen binary is available, and runs it to generate the project. If the user asks for features progen doesn't support natively, generate the base project first, then add those features on top of the generated code.

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Build or resume mathematical-modeling competition work, including CUMCM, MCM/ICM, graduate and regional contests, data challenges, and open-topic statistical modeling. Guide problem framing, modeling, computation, validation, Chinese or English LaTeX writing, and reviewed PDF/source delivery using current official requirements. Not for ordinary paper polishing.

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Layered technical-writing standard: Diátaxis structure, Google developer style sentences, STE instruction rules, Global English syntax. Use for /technical-writing or when writing or reviewing docs, RFCs, readmes, PR descriptions, or commit messages.

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Browser Use is an open-source Python library that lets an LLM agent drive a real browser to navigate sites, fill forms, click and extract data from a plain-English task. Use when the user wants an AI agent to automate a website, scrape pages that need clicking or login, return structured data from the web, add browser tools to a coding agent, or run browser agents locally or in the cloud.

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Axiom — First-Principles Assumption Auditor / 第一性原理拆解器 workflow skill. Use this skill when the user needs First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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。

Axiom — First-Principles Assumption Auditor / 第一性原理拆解器 workflow skill. Use this skill when the user needs First-principles assumption auditor. Classifies each hidden assumption (fact / convention / belief / interest-driven), ranks by fragility × impact, and rebuilds conclusions from verified premises. Bilingual: auto-detects Chinese or English and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.

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Use when text must be easy for its intended reader to find, understand, and act on — reports, emails, documentation, UI text, announcements, explanations, AI output that reads as dense or bureaucratic. Applies ISO 24495-1 plain language principles with dedicated technique layers for English and Traditional Chinese. Triggers: plain language rewrite, apply ISO 24495, make this clearer for readers, de-jargon this, 淺白改寫, 白話改寫, 去公文腔, 讓讀者一次看懂. Not for creative or literary writing.

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Adds a searchable text layer to a scanned PDF with ocrmypdf. Installs the toolchain at runtime in ~18s. Use when a PDF's pages are images and the deliverable is a file to keep, grep, or hand to another tool: 'make this PDF searchable', 'OCR this scan', 'I can't select the text in this PDF', 'search across these scanned pages', 'the pdf skill returned nothing'. Handles non-English scans via tesseract language packs. NOT for charts, diagrams, handwriting, or slide layouts. Route those to transcribing-images.

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Edit English prose for clarity, specificity, natural flow, and fit to the requested voice. Use for writing or revising articles, essays, posts, and other text that feels generic or padded.

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Write algorithm-optimized captions/descriptions for social media posts and reels. Supports Instagram (Reels, Feed, Carousel), TikTok, Threads, Facebook, and YouTube Shorts. The user sends material (text, image, script, competitor post, screenshot) and gets ready-to-use captions for ALL platforms at once, in English. Use when asked to "write a caption", "write a description", "caption for instagram", "описание к посту", "подпись для рилса", "описание для тикток", "caption for reels", "social media post", or any caption/description writing task. Also triggers when user sends an image, screenshot, or text and says something like "сделай описание", "напиши подпись", "caption this", "описание для этого".

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Use when the user asks what an American/British TV show or movie line, catchphrase, idiom, or slang means — "这句美剧台词什么意思", "XX 是什么梗", "老友记里那句…", "为什么这么说", "这个口头语怎么用", "what does 'X' mean in this show", or pastes a subtitle line / screenshot / SRT and wants the spoken English explained. Explains meaning, origin (why people say it), tone & offensiveness, when you can/can't use it, natural Chinese equivalent, examples, scene context, how to respond, and logs it to a personal 生词本. Triggers — "美剧口头语", "台词什么意思", "这是什么梗", "/wjs-explaining-tv-slang".

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Use when the user has an SRT (or transcript text) in one language and wants it translated to another, with punctuation-bounded re-segmentation so cues end at real sentence breaks. Simplified Chinese (zh-CN) and English (en) are first-class targets; other targets follow the same rules. Outputs a target-language SRT or bilingual SRT — no audio, no burn-in. Triggers — "翻译字幕", "翻成中文", "translate this SRT", "中英双语字幕", "把这个 SRT 翻译成 X", "bilingual 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。

Use when the user has audio or video and wants a timestamped transcript (SRT) in the source language. Routes by source language — Chinese defaults to Volcano (豆包) ASR; other languages (Spanish, English, Portuguese, French, Italian, Japanese, Korean, etc.) use OpenAI Whisper API with word-level timestamps and self-assembled cues. Outputs SRT with punctuation-bounded cues capped for on-screen reading. Triggers — "转写", "转成字幕", "做 SRT", "transcribe", "make subtitles", "speech to text", "出字幕".

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Applies the reasoning of Mary Wollstonecraft (18th-century English philosopher and author of A Vindication of the Rights of Woman) to evaluate situations involving power dynamics, education, independence, gender roles, and systemic inequality. Use this skill whenever Claude encounters career trade-offs involving financial dependence, analyzing structural oppression, questioning societal norms, or balancing reason against emotion. It helps dismantle arbitrary hierarchies, prioritize rational capability over superficial elegance, and frame personal struggles as political realities.

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Shape output for a reader with ADHD, then write each sentence in controlled English: action first, one word one meaning, active voice, simple tenses, state restated every turn. Invoke with /attention-control; stays on until "stop attention control".

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This skill should be considered when you need to normalize testing engineers' written defect reasons following the provided product codebooks. This skill will correct the typos, misused abbreviations, ambiguous descriptions, mixed Chinese-English text or misleading text and provide explanations. This skill will do segmentation, semantic matching, confidence calibration and station validation.

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模拟高三英语辅导老师，辅导英语阅读理解、完形填空、语法填空、写作等问题。重语言能力培养、做题技巧、词汇积累。当学生提出英语问题、请求讲解语法、分析阅读题、修改作文时使用。

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Write and edit Brazilian Portuguese prose with natural rhythm and the author's voice while preserving facts, meaning, and intent. Use for PT-BR requests to humanizar, tirar cara de IA, remover AI slop, reescrever com voz, simplify language, or write a post, email, article, or bio. Also use the author's notes or transcripts and ask targeted questions when essential facts are missing. For English text, use the bundled human-ai skill.

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Start a new prospect's intake, with or without their files in hand — a request naming a new prospect and attaching no documents is a normal starting point, because Step 1 searches the connected tools or asks the advisor to upload. Cleans and normalizes their account files (statements, exports, screenshots) into a consolidated view, then hands back a plain-English prospect summary, a detailed analyst handoff the full proposal gets built from, and a friendly "what to expect" memo, offered as a Gmail draft on approval. Does not produce the proposal, recommend an allocation, or quote fees. Triggers on "prospect intake", "/prospect-intake", "new prospect intake", "clean up [prospect]'s statements", "process [prospect]'s files", "what to expect note for [prospect]" — and on how an advisor raises a new prospect before any file exists: "I met with a potential client/customer", "[name] is interested in becoming a client", "I have a new prospect", "how should I proceed with [name]".

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Turn an English description (or mermaid source) into a diagram triplet: the source, an editable .excalidraw file you can open on excalidraw.com, and rendered SVG + PNG. (gstack)

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Modify a classroom task with language scaffolds that preserve cognitive demand for EAL learners. Use when adapting existing tasks for students at different English proficiency levels.

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。