리서치·학습 스킬

Capture Elixir/Ecto/LiveView lessons and Hex API rules. Use after corrections or when asked to document learning, record a lesson, prevent a fixed mistake, or remember package guidance with --library.

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Walk through the Elixir/Phoenix plugin commands, workflow, and features in 6 interactive sections. Use when a new user wants to learn what the plugin offers or needs a refresher on available commands.

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Self-improving loop for plugin skills. Reads program.md, proposes one mutation per iteration, evaluates against deterministic scorer, keeps improvements via git, reverts failures. Targets weakest skill+dimension. Use with /loop for overnight runs.

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Intent-driven spec precipitation — state a constraint in natural language (加一条规范：禁止用 any / 记录架构约束：服务间走 gRPC / 质量规则：覆盖率≥80%) and the workflow infers the category and records a <spec-entry>. Spec = 项目约束规则（编码规范、架构约束、质量标准）；可复用知识文档走 /maestro-knowhow capture。Triggers on "maestro-spec add", "记录规范", "添加约束", "添加规则", "加一条规范", "spec add". Terminology：spec = project constraints/rules (<spec-entry>). Reusable knowledge documents use /maestro-knowhow capture. Learning discoveries from /maestro-learn use <learning-entry> tags in learnings.md (separate from spec entries).

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Research ideation workflow from literature search to research planning. Triggers on "brainstorm research ideas", "identify research gaps", "conduct gap analysis", "start research project", "conduct literature review", "define research question", "select research method", "plan research", "research ideation".

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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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User-invoked learning toolkit — guided reading, investigation, pattern extraction, or second opinions. Manual `/maestro-learn` only; NEVER auto-invoke for code exploration or analysis — route those intents to the analyze step via /maestro-next

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Systematic academic paper review workflow covering self-review before submission and rebuttal writing after receiving reviewer feedback. Triggers on "review paper", "self-review", "write rebuttal", "respond to reviewers", "analyze review comments", "paper review".

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Enhanced academic paper review response workflow with Agy/CLI collaborative analysis and multi-perspective discussion. Produces structured rebuttal documents with evidence-based strategies. Triggers on "rebuttal", "respond to reviewers", "review response", "审稿回复".

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Four-layer citation verification for academic papers. Scans LaTeX/BibTeX files, verifies every citation via WebSearch and Google Scholar, generates verification report with fix suggestions. Triggers on "verify citations", "check references", "citation verification", "prevent fake citations", "引用验证".

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This skill should be used only when the user explicitly asks to use `$ralph-specum-research`, or explicitly asks Ralph Specum in Codex to run the research phase.

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.omd/preferences.md의 status:pending 항목을 Core v2 System Graph에 합쳐 DESIGN.md를 재생성하고 status를 applied로 플립. '프리퍼런스 정리해줘', 'fold preferences', 'apply all corrections', 「好みをDESIGN.mdに反映」, 「套用偏好」류의 요청에 트리거. 단발성 교정 기록은 omd:remember.

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One effect, done well: 먹 번짐 — a large Korean, Japanese or Chinese display headline that reads as sumi ink printed on hanji. The heading stays real, selectable DOM text in ink color from the first frame; a WebGL2 layer over it adds what real ink does: a wet, glossy stroke with a soft bloom that shrinks as it dries, ink pooling darker at stroke rims, ends and corners, paper fibers showing through thick strokes, and capillary feathering along fibers at a few edges only. Two parameters (bleed, duration), ~5 KiB gzip of library JS, procedural paper texture, static fallback, prefers-reduced-motion, real-GPU verification script. Use for a CJK hero/launch headline, brand title, campaign line or section opener that should feel like a printed calligraphy poster. Triggers: '먹 번짐', '잉크 번짐', '한지 느낌 제목', '한글 타이포 셰이더', '제목에 셰이더', '墨のにじみ', '和紙', '筆文字っぽく', '墨跡暈開', '宣紙', 'CJK headline shader', 'sumi ink text effect', 'ink bleed text', 'Hangul shader'. Not for body text, buttons, or Latin-only headlines. Full-page shader backgrounds → omd-shader-hero. Korean typesetting rules → hangul. Brand tokens → omd-apply.

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One effect, done well: 먹 번짐 — a large Korean, Japanese or Chinese display headline that reads as sumi ink printed on hanji. The heading stays real, selectable DOM text in ink color from the first frame; a WebGL2 layer over it adds what real ink does: a wet, glossy stroke with a soft bloom that shrinks as it dries, ink pooling darker at stroke rims, ends and corners, paper fibers showing through thick strokes, and capillary feathering along fibers at a few edges only. Two parameters (bleed, duration), ~5 KiB gzip of library JS, procedural paper texture, static fallback, prefers-reduced-motion, real-GPU verification script. Use for a CJK hero/launch headline, brand title, campaign line or section opener that should feel like a printed calligraphy poster. Triggers: '먹 번짐', '잉크 번짐', '한지 느낌 제목', '한글 타이포 셰이더', '제목에 셰이더', '墨のにじみ', '和紙', '筆文字っぽく', '墨跡暈開', '宣紙', 'CJK headline shader', 'sumi ink text effect', 'ink bleed text', 'Hangul shader'. Not for body text, buttons, or Latin-only headlines. Full-page shader backgrounds → omd-shader-hero. Korean typesetting rules → hangul. Brand tokens → omd-apply.

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.omd/preferences.md의 status:pending 항목을 Core v2 System Graph에 합쳐 DESIGN.md를 재생성하고 status를 applied로 플립. '프리퍼런스 정리해줘', 'fold preferences', 'apply all corrections', 「好みをDESIGN.mdに反映」, 「套用偏好」류의 요청에 트리거. 단발성 교정 기록은 omd:remember.

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Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning). Supports SFT, DPO, GRPO, KTO, RLOO and Reward Model training via CLI commands.

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Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.

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Look up and read Hugging Face paper pages in markdown, and use the papers API for structured metadata such as authors, linked models/datasets/spaces, Github repo and project page. Use when the user shares a Hugging Face paper page URL, an arXiv URL or ID, or asks to summarize, explain, or analyze an AI research paper.

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Agents should invoke this skill for academic or technical papers, arXiv/PubMed/IEEE/ACM links, PDFs, methodology review, limitations, practical implications, or extracting findings for engineering decisions.

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文献引用标记移除工具。读取含引用标记的文本，移除数字型、作者年份型和上标型引用标记，保留正文语义并输出清理后的文本。 当用户提到移除引用标记、清理参考文献标注、删除文献引用等需求时使用此skill。 适用于科研论文、学术文档的文本清洗，不负责参考文献章节重写、文献内容解析或非引用括号内容的系统抽取。

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Use when the user needs to turn a real software engineering / computer science project and an existing thesis draft into a submission-ready undergraduate thesis manuscript. Trigger for requests such as "根据项目把论文改成定稿", "按学校模板排版成最终版", "复制初稿后生成定稿 Word", "为定稿降查重", "根据PaperPass报告降AIGC", "继续在手改初稿上改", "恢复原来的图表和数据库说明", or when academic-paper-strategist has already produced an evidence-backed rewrite plan. Outputs a cleaned manuscript, final DOCX workflow, and a separate rework report.

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Use when the user needs to plan, de-risk, or ground a software engineering / computer science undergraduate thesis from a real codebase before final writing. Trigger for requests such as "根据项目写毕业论文", "先做论文大纲", "用真实项目材料规划论文", "检查论文是否脱离代码", "根据检测报告降查重", "根据AIGC报告改写定稿", "继续在手改初稿上改", or when an existing draft thesis must be reworked against a school format sample. Produces an evidence-backed outline, chapter rewrite plan, figure plan, and handoff package for academic-paper-composer.

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Show how vibecosystem works - agents, skills, hooks, and self-learning pipeline.

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Pre-search topic resolution. Maps vague queries to concrete entities (GitHub orgs, X handles, subreddits, docs URLs) before searching. Run as first step of any research workflow to dramatically improve search precision.

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