fivetaku

Extract a real design system from a live URL into `design.md` and `report.ko.html`, or reuse the bundled multi-site design corpus as a deterministic design brief. Use when the user wants real CSS tokens, a reusable design reference, or a design pack that can feed apply/build flows.

Structured research-query builder for turning a vague topic into a research brief and machine-readable query before full deep research starts. Use when the user wants help framing a research request.

Comprehensive, citation-heavy research workflow with session state, structured outputs, and source-quality checks. Use when the user explicitly asks for deep research, a long-form report, or citation-backed analysis on a topic.

Fetch and explain official documentation for libraries, frameworks, and tools using llms.txt-first retrieval and official-source fallbacks. Use when the user wants official docs, version-aware references, or an explanation grounded in primary documentation.

Explain Git and GitHub concepts using cloud-folder analogies for non-developers. Use when the user asks "commit이 뭐야?", "push랑 commit 차이", "PR이 뭐야?", "branch가 뭐야?", "깃 용어", "도움말", or similar beginner Git questions.

Create a beginner-friendly GitHub Pull Request workflow. Use when the user says "PR 만들어줘", "검토 요청", "리뷰 요청", "팀원한테 보여주고 싶어", "create PR", or "pull request".

Stage and commit changed files with beginner-friendly Korean explanations. Use when the user says "저장해줘", "커밋", "변경 내용 저장", "save", or "commit".

Help non-developers install Git, authenticate GitHub CLI, and create or connect a repository. Use when the user says "깃 시작", "깃 설정", "처음이에요", "git 설치", "GitHub 연결", "프로젝트 만들기", or "git setup".

Complete, populate and fill out 3-statement financial model templates (Income Statement, Balance Sheet, Cash Flow Statement). Use when asked to fill out model templates, complete existing model frameworks, populate financial models with data, complete a partially filled IS/BS/CF framework, or link integrated financial statements within an existing template structure. Triggers include requests to fill in, complete, or populate a 3-statement model template

Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model, including financial-model integrity checks like BS balance, cash tie-out, and logic sanity. Triggers on "audit this sheet", "check my formulas", "find formula errors", "QA this spreadsheet", "sanity check this", "debug model", "model check", "model won't balance", "something's off in my model", and "model review".

Clean up messy spreadsheet data — trim whitespace, fix inconsistent casing, convert numbers-stored-as-text, standardize dates, remove duplicates, and flag mixed-type columns. Use when data is messy, inconsistent, or needs prep before analysis. Triggers on "clean this data", "clean up this sheet", "normalize this data", "fix formatting", "dedupe", "standardize this column", and "this data is messy".

Build institutional-grade comparable company analyses with operating metrics, valuation multiples, and statistical benchmarking in Excel/spreadsheet format.

Real DCF (Discounted Cash Flow) model creation for equity valuation. Retrieves financial data from SEC filings and analyst reports, builds comprehensive cash flow projections with proper WACC calculations, performs sensitivity analysis, and outputs professional Excel models with executive summaries. Use when users need to value a company using DCF methodology, request intrinsic value analysis, or ask for detailed financial modeling with growth projections and terminal value calculations.

This skill should be used when completing LBO (Leveraged Buyout) model templates in Excel for private equity transactions, deal materials, or investment committee presentations. The skill fills in formulas, validates calculations, and ensures professional formatting standards that adapt to any template structure.

Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.

Updates a presentation with new numbers — quarterly refreshes, earnings updates, comp rolls, rebased market data. Use whenever the user asks to "update the deck with Q4 numbers", "refresh the comps", "roll this forward", "swap in the new earnings", "change all the $485M to $512M", or any request to swap figures across an existing deck without rebuilding it.

AI-collaboration mentoring — coaches users on request quality, anti-patterns, and concepts across 4 modes, analyzed via v2 level system (6 axes × 7 levels, 0.5 increments). Korean triggers: "멘토링해줘", "코칭해줘", "요청 코칭해줘", "뭘 잘못하고 있는지", "어떻게 요청하면 좋을지". English triggers: "mentor", "coach", "coaching", "improve my requests".

Growth report generator — analyzes AI-collaboration session data and produces a progression report using the v2 level system (6 axes × 7 levels, 0.5 increments). Korean triggers: "성장 리포트", "성장 분석", "얼마나 성장했는지", "레벨 체크", "성장 트래킹". English triggers: "growth report", "growth tracking", "level check".

Vibe-sunsang knowledge base — answers questions about the level system (v2 6-axis × 7 levels), anti-patterns, and workspace types. Korean triggers: "바선생 안티패턴이 뭐야?", "바선생 레벨 시스템 설명해줘", "6축이 뭐야?", "바선생 성장 지표". English triggers: "vibe-sunsang levels", "anti-patterns", "workspace types".

Vibe-sunsang initial setup — guides through workspace creation, project linking, type classification, and first conversion. Korean triggers: "바선생 시작", "온보딩", "초기 설정", "초기화", "셋업". English triggers: "onboarding", "init", "setup", "start vibe-sunsang".

Conversation-log converter — transforms Claude Code JSONL logs into Markdown and provides an analysis guide. Korean triggers: "변환", "대화 변환", "로그 변환", "회고", "이번 주 대화". English triggers: "retro", "convert conversations", "log conversion".

This skill should be used when the user asks to "이미지 만들어줘", "그림 생성해줘", "이미지 그려줘", "썸네일 만들어", "로고 만들어줘", "일러스트 그려줘", "포스터 만들어", "프로필 이미지", "배너 만들어", "아이콘 만들어", "표지 이미지", "image generate", "create image", "make thumbnail", "make logo", "make illustration", "draw image". Also trigger on casual expressions like "그림 하나 뽑아줘", "이미지 좀 만들어봐", "비주얼 만들어줘". DO NOT trigger on code-generation requests like "함수 만들어줘", "컴포넌트 만들어줘", "페이지 만들어줘" — those are for /pumasi (parallel coding), not this skill.

Parallel coding orchestration — Claude takes the PM/architect role, Codex CLI instances act as parallel outsource developers. Auto-triggers when 3+ independent modules need concurrent implementation. Distributes subtasks to Codex, then Claude reviews and integrates. Korean triggers: "/pumasi", "품앗이로 만들어줘", "품앗이 켜줘", "codex 외주로", "codex한테 시켜". English triggers: "pumasi", "parallel with codex", "delegate to codex", "codex outsource".

This skill should be used when a user requests deep research on any topic. Example queries include "/deep-research", "deep research on", "리서치해줘", "딥리서치", "심층 연구", "[주제]에 대해 리서치해줘".

This skill should be used when a user wants to build a structured research query interactively before starting deep research. Example queries include "/deep-research query", "리서치 쿼리 만들어줘", "research query builder", "structured research query", "쿼리 빌더".

Auto-bypass for blocked websites — tries every method until one works. Use when WebFetch returns 402/403/blocked, or when accessing X/Twitter, Reddit, YouTube, GitHub, Mastodon, Medium, Substack, Stack Overflow, Threads, Naver, Coupang, LinkedIn, or any platform with WAF/bot protection. Leverages yt-dlp (1,858 media sites), Jina Reader, public APIs (HN, Bluesky, arXiv), and a generic WAF-profile-driven fetch chain (curl_cffi TLS impersonation, mobile URL transforms, Playwright real-Chrome) with auto dependency install. Korean triggers: 트위터/X 못 열어, 레딧 안 읽혀, 유튜브 자막 뽑아줘, 깃헙 검색, 사이트 차단됨, 스레드 안 열려, 마스토돈, 미디엄, 서브스택, 스택오버플로우, 네이버 블로그, 디시인사이드, 에펨코리아, 요즘IT, 긱뉴스, 클리앙, 쿠팡, 링크드인, 당근마켓. English triggers: twitter access, reddit blocked, youtube subtitles, github search, arxiv papers, threads, mastodon, medium, substack, stackoverflow, naver blog, dcinside, fmkorea, coupang, linkedin, yozm, wishket. Do NOT trigger for simple web searches that WebSearch can handle directly.

This skill should be used when the user asks to "콘텐츠 만들어줘", "카드뉴스 만들어줘", "카드뉴스 영상 만들어줘", "리서치부터 영상까지", "콘텐츠 파이프라인", "content pipeline", "주제로 콘텐츠 만들어줘". 주제 하나로 리서치→카드뉴스→영상까지 풀 파이프라인을 자동 실행합니다. Make sure to use this skill whenever the user mentions content creation that involves research, card news, or video generation from a topic.

This skill should be used when a user asks about the llms.txt standard, wants to find or fetch official documentation for a library or framework, or discusses documentation accessibility for AI systems. Example queries include "llms.txt란 뭐야", "React 공식 문서 찾아줘", "fetch the Next.js docs", "documentation for LLMs", "AI용 문서 접근성", "라이브러리 문서 가져와", "which sites have llms.txt", "공식 문서 URL 알려줘", "docs index for Stripe".

This skill should be used when the user asks to "스킬 만들어줘", "에이전트 만들어줘", "커맨드 만들어줘", "스킬러들의 수다", "수다", "skill builder", "make a skill", "create a skill", "build a skill".

This skill should be used when the user asks to "뉴스레터 만들어줘", "뉴스 정리해줘", "최신 뉴스 검색해줘", "뉴스 요약해줘", "뉴스 모아줘", "news newsletter", "뉴스 브리핑". 네이버 뉴스 검색 API로 24시간 내 최신 뉴스를 수집하고, 보기 좋은 HTML 뉴스레터로 만들어줍니다. Make sure to use this skill whenever the user mentions news collection, news summary, or newsletter creation.