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Found 1,051 Skills
Packages generated wiki Markdown into a VitePress static site with dark theme, dark-mode Mermaid diagrams with click-to-zoom, and production build output. Use when the user wants to create a browsable website from generated wiki pages.
USE FOR getting AI-generated POI text descriptions. Requires POI IDs obtained from web-search (with result_filter=locations). Returns markdown descriptions grounded in web search context. Max 20 IDs per request.
Use this skill for multi-model AI code review. Trigger whenever the user asks to review code changes, audit a diff, check code quality, review a PR, review commits, or review uncommitted changes before pushing or merging. Also trigger when they say 'code review', 'review my changes', 'check this before I merge', or want multiple perspectives on code. Runs Codex and Claude reviews in parallel, then synthesizes a unified report. Do NOT use for reviewing documentation, markdown, or non-code files, or for trivial single-line changes.
Neovim (LazyVim) configuration via Nix: LSP, plugins, im-select, extraPackages. Mason is disabled; all LSP/formatters/linters are managed by Nix extraPackages. Triggers: "nvim 플러그인", "lazy.nvim", "한글 입력", "im-select", "extraPackages", "Mason 비활성화", "tree-sitter 빌드 오류", "LSP 서버 안 됨", "markdownlint", "Neovim 설정", Mason migration, tree-sitter build errors, lazy-lock.json conflict.
Generate an Information Architecture (IA) document from a service plan, PRD, or product idea. Outputs a structured screen hierarchy as Markdown nested lists and saves to SCREENS.md.
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.
High-quality article translation skill, adopting a four-step professional translation workflow: **Analysis → Initial Translation → Review → Final Draft**. Only supports Chinese ↔ English, Chinese ↔ Japanese translation. Triggered when users explicitly request translation using terms such as "翻译", "translate", "精翻", "翻訳", "翻译文章", "translate to Chinese/English/Japanese", "改成中文", "改成英文", "改成日文", "翻成中文", "翻成日文", "翻成英文", "英译中", "中译英", "中译日", "日译中", "日本語に翻訳", "中国語に翻訳", "英語に翻訳", "これを翻訳して", "put this in Chinese", "put this in English", "put this in Japanese", "convert to Chinese", "convert to English", "convert to Japanese", "帮我翻一下", "本地化", "localize", "这篇文章翻译一下", or provide a URL/file/text body and explicitly request a final draft in the target language. Not applicable to requests for only summarization, explanation, comprehension, or organization. If the input is a URL, prioritize using `curl -L` to request `r.jina.ai` to fetch the body content in Markdown; if fetching fails or the content is incomplete, you must stop immediately and ask the user to provide the full text themselves.
Convert a PDF (research paper, report, or any document) into a polished multi-slide HTML presentation with a structured outline JSON and summary markdown. Trigger this skill when the user mentions making slides or a PPT from a PDF — in Chinese or English.
A step-by-step practice tool for LeetCode medium-difficulty interview questions. It is triggered when users want to practice algorithm problems, brush up on LeetCode, prepare for technical interviews, or say "Give me a problem", "Next problem", "Generate scaffold", "Start practicing". It supports categorized practice by problem type (DP, Linked List, Tree, Graph, Sliding Window, Two Pointers, Hash Table, Binary Search, Stack, Heap, Backtracking, Interval, String, Union Find), generates Python scaffolds with test cases for each problem, tracks learning progress via Markdown tables, and guides users to think independently before providing solutions. It supports the goal of 3 problems per day, counts progress via `git diff README.md` and submits to Git.
Build a retrospective or forward-looking work timeline from git commits, project docs, user notes, or chat records, then output a Markdown and/or HTML report with a Gantt chart or timeline visualization. Use when the user wants to review past work across one or more projects, explain time allocation to a mentor, summarize what was done in a period, or plan the next phase with a timeline.
Use when the user asks to review code, review changes, review a commit, review a PR, audit code quality, check for security issues, or generate a code review report. Trigger on phrases like "review my changes", "코드 리뷰", "check my code", "review the last commit", "what do you think of this diff", "compare branches", "code audit" — even if they don't say "code review" explicitly. For persistent file output use `code-review-md` (markdown) or `code-review-html` (markdown + HTML).
Look up the public API of any JVM dependency (Scala 3, Scala 2, Java) from the terminal — type signatures, members, docs, and source as Markdown, no JAR unpacking needed. Use this skill whenever you need to call an unfamiliar library method, explore a package's types, or check a dependency's API. Prefer cellar over Metals MCP only for looking up external dependency APIs (`cellar get-external` vs Metals `inspect`/`get-docs`) — cellar needs no project import and queries any published Maven artifact. For everything else (references, rename, goto definition, diagnostics, compile), use Metals.