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Run the proofreading protocol on academic writing — papers or manuscripts. Checks grammar, typos, layout issues, consistency, and academic writing quality. Produces a report without editing files. Make sure to use this skill whenever the user wants surface-level writing errors found — not substantive academic critique. Triggers include: "proofread", "check for typos", "grammar check", "look for errors in my draft", "proofread all", "polish this", "check my writing", "are there any mistakes", "proofread before I send this", or when the user wants a clean-up pass rather than feedback on arguments or methods.

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Verify research idea novelty against recent literature. Use when user says "查新", "novelty check", "有没有人做过", "check novelty", or wants to verify a research idea is novel before implementing.

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Remove AI writing patterns from prose. Use this skill when writing, drafting, editing, reviewing, or revising any text to eliminate predictable AI tells, slop, and formulaic patterns. Trigger this skill whenever the user asks to "deslop", "de-AI", "make it sound human," "remove AI patterns," "remove AI tropes," "clean up AI writing," fix "slop," "deslop" text, or review prose for authenticity. Also use when the user asks you to write or draft anything and wants it to sound natural rather than AI-generated. Common use cases include scientific writing (manuscripts, abstracts, cover letters, grant narratives, discussion sections, peer review responses), blog posts, newsletters, memos, reports, and any other substantial prose.

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Polish English academic papers for SSCI journal submission. This skill checks grammar, improves readability, and enhances academic tone. Use when the user asks to polish, proofread, edit, or improve their English academic paper, manuscript, or article — especially when targeting SSCI, SCI, or other international journals. Also use when the user asks to "润色", "修改语法", "提升学术性", "polish my paper", or mentions their paper needs language improvement for journal submission. Always trigger on any request involving academic English polishing, even if the user doesn't explicitly say "SSCI."

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Apply the ScholarEval framework to systematically evaluate scholarly work across quality dimensions (novelty, rigor, significance, and clarity). Use to critique academic papers, research proposals, literature reviews, or grant applications and produce a structured, criterion-based assessment.

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Perform an exhaustive, multi-pass proofread and copy-edit of an applied-microeconomics manuscript to top-economics-journal standards (AER, QJE, Econometrica, ReStud), checking prose, equations, table notes, footnotes, and citations for avoidable errors. Use before submitting or circulating an empirical economics paper.

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Detect and humanize AI-generated Chinese text. 20+ rule detection categories plus statistical features (sentence-length CV, short-sentence fraction, comma density, perplexity, GLTR, DivEye) plus scene-aware LR fusion (rule × 0.2 + LR × 0.8) trained on three scenes: general / academic / longform 长文本 (≥1500 字)。Unified CLI: ./humanize {detect,rewrite,academic,style,compare}. 8 style transforms (casual/zhihu/xiaohongshu/wechat/academic/literary/weibo/novel)。 Multi-paragraph rewriting (paragraph length CV、跨段 trigram 重复) plus best-of-N humanize (默认 N=10 取最低 LR)。165 replacement patterns + CiLin 同义词词林 38873 with collision blacklist。 Academic paper AIGC reduction for CNKI/VIP/Wanfang (知网/维普/万方 AIGC 检测降重)。 Pure Python, no dependencies, offline。v5.0.0 — HC3 fused 准确率 95%、学术 hero 100→35 (-65)、 工作汇报 96→13 (-83)、长篇博客 96→41 (-55)。 Use when user says: "去AI味", "降AIGC", "人性化文本", "humanize chinese", "AI检测", "AIGC降重", "去除AI痕迹", "文本改写", "论文降重", "知网检测", "维普检测", "AI写作检测", "让文字更自然", "detect AI text", "humanize text", "reduce AIGC score", "make text human-like", "去ai化", "改成人话", "去机器味", "降低AI率", "过AIGC检测", "长文本改写", "小说改写"

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Generate beautiful interactive timeline HTML pages from JSON data, with vertical, horizontal, or dual-side layouts, collapsible details, and custom colors. Ideal for project milestones, company histories, or resumes. Triggered when a user mentions 'timeline', 'history of events', 'project milestones', 'release log', or asks to visualize a chronological sequence of data.

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How to work in a Worldbuilding project (the `worldbuilding` starter pack): a fiction encyclopedia of characters, settings, themes, factions, and lore. Read when the project has these folders, OR when asked to add a character, setting, faction, or piece of lore, or to check the world for internal consistency. Carries the auto-stub and consistency behaviors so that guidance does not live inside template bodies or folder descriptions. Complements the platform `open-knowledge` skill; does not replace it.

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Plan and build 2D game maps and scenes - top-down and side-scrolling levels, tilemaps, prop packs, parallax backgrounds and HD-2D battle or story plates - with collision, navigation and reachability checks, environment motion, a playable HTML preview and export to Tiled, Godot 4 or LDtk. Map art (terrain, tiles, props, plates, parallax layers) is image generation by default, through generate2dmedia route_media.py (the API when a key is configured, else the local Codex or Grok CLI); map data (layout, collision, exits, spawns) is written as data. Use for any map, level, room, scene, background, terrain or prop-kit request. Not for characters, creatures, items or FX (generate2dsprite), character animation (video2dsprite), code-drawn tiles or maps (codeart2d, only on request) or calling an image or video API by itself (generate2dmedia).

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Coordinate project or repository renames and moves involving Git, BB, services, or multiple machines. Preserve work and history while updating operational paths. Excludes ordinary file, code-symbol, and thread-title renames.

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Activate for OSS adoption work -- README conversion surfaces, quickstart, templates, release announcements, contributor funnel, story angles -- and any update to the maintained growth strategy at WIP/growth-strategy.md.

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Create user-facing App Store release notes by collecting and summarizing all user-impacting changes since the last git tag (or a specified ref). Use when asked to generate a comprehensive release changelog, App Store "What's New" text, or release notes based on git history or tags.

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Write SEO-optimized blog posts, landing pages, and content improvements following Google's E-E-A-T and Helpful Content guidelines. Handles new content creation from a keyword or topic, and improving existing pages. Use when asked to "write a blog post", "create a landing page", "improve this page", "write content about X", "content for keyword X", "draft an article", "blog post about", "landing page for", "service page", "product page copy", "rewrite this page", "make this page rank better", "content brief", "how-to guide", "listicle", or any content creation or improvement task for a website.

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分章节创作引人入胜的中文小说。支持各种题材（悬疑/言情/奇幻/科幻/历史等），支持10-50章长篇创作，每章3000-5000字，结尾设置悬念钩子。强调深度润色去除AI痕迹，确保文字自然流畅。 当用户要求：写小说、创作故事、分章节写作、连续剧情、章节悬念、长篇小说时使用。

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Investigate fast-agent session and history files to diagnose issues. Use when a session ended unexpectedly, when debugging tool loops, when correlating sub-agent traces with main sessions, or when analyzing conversation flow and timing. Covers session.json metadata, history JSON format, message structure, tool call/result correlation, and common failure patterns.

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知乎问答回答发布：在知乎问题下发布原创回答——搜热门问题、检查可答性、写内容、 Playwright 发布（绕 header 遮挡 + JS 遍历发布按钮）。当用户说"回答知乎问题""在知乎问答下回答" "发知乎回答""知乎答题""帮我回答这个知乎问题""批量回答知乎"时使用。与 skill-zhihu-publisher 区别：那个发**专栏文章**（zhuanlan），本 SKILL 专发**问答区的回答**；回答内容写作用制作层 SKILL （novel-writer / copywriting）。

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长篇小说/网文连载创作：从世界观、人设和三级大纲写到逐章正文，并用文件化状态维护伏笔、前情和跨章一致性。 当用户说“写小说/网文/盐选故事、连载、续写下一章、小说大纲、人物设定、世界观、黄金三章”时使用。 通用文章用 article-outline/social-content；单段改风格或润色用 style-transfer/text-polisher。

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Turns an answer into a one-page visual HTML explainer: the model writes a short Markdown draft and the bundled CLI builds one page. Use it proactively and liberally, without being asked, whenever a page would help the reader more than plain text, even if plain text would also work: any explanation of how something works or how parts relate (flow, request path, architecture, code or folder structure, state machine, lifecycle, history); any comparison, trade-off or decision with pros and cons; any diagnosis, review or investigation, especially with several causes or findings to rank; any answer with a table, a numbered or ranked list, steps, branches or several sections; or when the user says "I don't get it / draw it / explain visually / 讲讲原理 / 没看懂 / 画个图". When in doubt, use it: a page is quick and cheap to make. Also for explainer videos ("make a video", "做个视频") and for changing its settings. Skip only for small talk, a trivial one-line answer, or when the user asks for plain text.

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Review chart choice, labeling, accessibility, and storytelling quality for existing visualizations. Use as an explicit/manual helper for critique and cleanup, not as the main owner for scientific figure production or general chart generation.

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Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

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Recall past conversations, preferences, project history, and decisions from ReMe in Claude Code, or check the ReMe connection.

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Refresh a LinkedIn profile for a job search from the user's own resume — pick and check the profile photo, crop it locally to LinkedIn, Slack and GitHub sizes, and write a headline and About section grounded in the resume, then check that LinkedIn, GitHub and the resume tell the same story. Use when the user asks to "update my LinkedIn", "write my LinkedIn headline/About", "is this a good LinkedIn photo", "resize my headshot for LinkedIn", or shares a resume or profile photo for job-search feedback. Uses the free ProfessionalHeadshot.io MCP for official photo specs and photo scores when connected; works without it.

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Post-mortem investigation for failed GSD workflows — analyzes git history, artifacts, and state to diagnose what went wrong

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